Tag: Latvia

Alcohol-Related Costs and Potential Gains from Prevention Measures in Latvia

20240226 Alcohol Prevention Measures Image 01

Latvia has the highest per capita registered alcohol consumption rate among EU and OECD countries (OECD, 2024). In this brief, we show that the total budgetary (direct) and non-budgetary (indirect) costs associated with alcohol consumption in Latvia in 2021 amounted to 1.3–1.8 percent of the GDP. Non-financial costs from alcohol abuse amounted to a loss of nearly 90 thousand years spent in good health and with a good quality of life. We assess the potential effects of five alcohol misuse prevention measures, all recognized by the World Health Organization (WHO) as effective in reducing harmful alcohol consumption – especially when implemented together. Our analysis focuses on the individual effects of each measure and shows that raising the minimum legal age for alcohol purchases and enforcing restrictions on alcohol advertising and marketing are likely to yield the largest reductions in alcohol-related costs, although these effects will take time to fully materialize.

Introduction

Alcohol consumption is an important risk factor for morbidity and premature death worldwide. It is associated with over 200 diagnoses recorded in the International Statistical Classification of Diseases and Related Health Problems (CDC, 2021), including liver diseases, injuries, malignancies, and diseases of the heart and circulatory system (WHO, 2018). Alcohol consumption at any level is considered unsafe (Burton & Sheron, 2018).

Globally, an average of 3 million people die each year due to alcohol-related harm, accounting for 5.3 percent of all deaths (Shield et al., 2020). In 2019, alcohol consumption was the main risk factor for disease burden in people between 25 and 49 years of age and the second most important risk factor in people aged 10-24 years (GDB, 2019).

Alcohol use is associated not only with health problems but also with social issues, posing risks to people’s safety and well-being. It causes harm not only to the individual but also to family members and society at large (Rehm & Hingson, 2013). Various sectors, including health, justice, home affairs, and social care agencies, are involved in preventing the consequences of alcohol misuse and reducing the harm this causes. This demonstrates the multiple negative impacts of alcohol use on public health and well-being (Flynn & Wells, 2013).

Latvia has the highest per capita registered alcohol consumption rate among the EU and OECD countries (OECD, 2024), and no clear trend of declining levels has been observed in recent years. Moreover, the consumption of spirits, which can potentially cause more harm than other alcoholic beverages (Mäkelä et al., 2011), is steadily increasing. According to WHO data (WHO, 2024), the high per capita consumption of registered absolute alcohol in Latvia, compared to other countries, is largely due to the consumption of spirits. In Latvia, the share of spirits in total consumption is around 40 percent. By comparison, in the Czech Republic and Austria, where total per capita alcohol consumption is similar to Latvian levels, spirits account for only 25 and 16 percent of total consumption, respectively, while the proportions of beer and wine are higher.

This policy brief reports the estimated costs related to alcohol use in Latvia in 2021, based on the study Alcohol Use, its Consequences, and the Economic Benefits of Prevention Measures (Pļuta et al., 2023). It also provides an overview of the expected benefits from implementing preventive measures, such as raising the minimum legal age for buying alcohol and restricting alcohol advertisements.

Costs of Alcohol Use in Latvia

We estimate three types of costs associated with alcohol consumption:

  • Direct costs: These include budgetary costs related to alcohol consumption, such as healthcare, law enforcement and social assistance costs, as well as expenses for public education.
  • Indirect costs: These costs represent unproduced output in the economy and arise from the premature deaths of alcohol users, as well as their reduced employment or lower productivity.
  • Non-financial welfare costs: This type of cost arises from the compromised quality of life of alcohol users, their families, and friends.

We estimate direct costs by utilizing detailed disaggregated data on alcohol-related budget costs in the healthcare sector, law enforcement institutions (including police, courts, and prisons), costs of public education (e.g., educating schoolchildren about the consequences of alcohol consumption), costs of awareness-raising campaigns, and social assistance costs. For cost categories that are only partially attributable to alcohol consumption, we classify only a fraction of these costs as attributable to alcohol use (e.g., liver cirrhosis is attributable to alcohol usage in 69.8 percent of the cases, so only this fraction of the budget costs on compensated medicaments is attributable to alcohol use). To estimate social assistance costs, including public expenditure on social services, sobering-up facilities, social care centres, orphanages, and specialized care facilities for children and out-of-family care, we conduct a survey among social assistance providers.

To estimate non-budgetary costs, we construct a counterfactual scenario where alcohol is not being overly consumed, ensuring higher productivity, a lower rate of unemployment, and lower mortality within the labour force. Finally, non-financial welfare costs are estimated by measuring the reduction in quality of life or QALYs lost (quality-adjusted-life-years) (for details, see the methodology section in Pļuta et al. (2023)).

The total direct and indirect costs of alcohol abuse in 2021 amounted to 1.3–1.8 percent of Latvia’s GDP. In comparison, revenues from the excise tax on alcoholic beverages in 2021 accounted for 0.7 percent of the GDP.

Direct costs, which entail expenses directly covered by the state budget, comprised 0.45 percent of the GDP. Among these costs, healthcare expenses were the largest component, constituting 37.8 percent  of total direct costs and 2.7 percent of general government spending on healthcare. Nearly half of these healthcare costs were attributed to the provision of inpatient hospital treatment for patients diagnosed with alcohol-related conditions. Another significant component of budgetary costs is associated with addressing alcohol abuse and combating illicit trade through law enforcement, accounting for 31.9 percent of total direct costs and 6.5 percent of general government spending on public order and safety.

Alcohol-related indirect costs amount to 0.9-1.3 percent of Latvia’s GDP. Despite not being directly covered by the state budget, they represent unproduced output and thus entail economic losses. The primary components of these indirect costs are linked to decreased output resulting from higher unemployment and reduced economic activity (0.6-0.8 percent of the GDP), as well as decreased output due to premature death among heavy drinkers (0.2-0.4 percent of the GDP). Notably, indirect costs attributed to alcohol misuse by males constitute almost two-thirds of the total indirect costs.

Finally, the non-financial costs from alcohol abuse in 2021 are estimated to reach 88 620 years spent in good health and with a good quality of life. These losses primarily stem from the distress experienced by household members from alcohol users, the decline in the quality of life among alcohol users themselves, and the premature mortality of such individuals.

The Effects of Preventive Measures

We consider five alcohol misuse preventive measures, all of which are included in the list of WHO “best buys” policies that effectively reduce alcohol consumption (WHO, 2017):

  • Reducing the availability of retail alcohol by tightening restrictions on on-site retail hours
  • Raising the minimum legal age for alcohol purchase from 18 to 20 years
  • Increasing excise tax on alcohol
  • Lowering the maximum allowed blood alcohol concentration limit for all drivers from 0.5 to 0.2 per mille (currently 0.2 for new drivers and 0.5 for all other drivers)
  • Restricting alcohol advertising and marketing

Our estimates of the expected reduction in alcohol-related costs resulting from these measures are based on two main components:

  • (1) our own estimates of alcohol-related costs in Latvia, as described above, and
  • (2) external estimates of the impact of the five misuse preventative measures on alcohol consumption derived from existing literature on other countries.

We then apply these external estimates to the calculated alcohol-related costs and Latvian data on alcohol consumption to determine the estimated impact for Latvia (for further details, see the methodology outlined in Pluta et al. (2023)).

Our findings indicate that the most substantial reduction in direct costs attributed to alcohol misuse is anticipated through raising the minimum alcohol purchase age to 20 years (yielding an 11.4-15.8 percent estimated cost reduction). Previous literature has shown that early initiation of alcohol use significantly increases the likelihood of risky drinking, and that risky drinking during adolescence significantly increases the risk of heavy drinking in adulthood (Betts et al., 2018; McCarty, 2004). Hence, raising the minimum legal age for alcohol purchase represents an effective tool to reduce alcohol consumption also among the adult population.

Another highly effective measure to reduce alcohol consumption is imposing restrictions on advertising, which results in a 5.0-8.0 percent estimated reduction of direct costs. There is a large body of literature indicating that alcohol advertising increases alcohol consumption among young people, as well as significantly increases the likelihood of alcohol initiation among adolescents and young adults (Noel, 2019; Jernigan et al., 2017). Also, among the adult population, alcohol consumption decreases with stricter advertising restrictions (see Casswell, 2022; Rossow, 2021).

However, it is important to emphasize that the full impact of both above discussed preventative measures will only manifest in the long run.

The Effect of Illicit Markets

It is often argued that illicit alcohol markets, which provide access to cheaper alternative alcohol than registered commercial markets, can limit the effectiveness of preventive measures on overall alcohol consumption (Rehm et al., 2022).

To explore the interplay between illicit alcohol circulation and alcoholism prevention measures we conduct semi-structured interviews with experts regarding the prevalence of illicit alcohol circulation in Latvia and strategies to mitigate it.

While our main findings emphasize the inherent challenge of precisely quantifying the size of the illicit alcohol market, our analysis suggests that the share of illicit alcohol in total alcohol consumption in Latvia is relatively low. We also conclude that the size of the illicit alcohol market has been diminishing in recent years, and that public interest in engaging with illicit alcohol is declining. Given these findings, the current scope of the illicit market is unlikely to substantially undermine the efficacy of alcohol control measures. This is especially true as the consumers of illicit alcohol represent a specific group minimally affected by legal alcohol control measures in the country.

Conclusion

Our findings underscore the substantial costs associated with the large alcohol consumption in Latvia. In 2021, budgetary (direct) and non-budgetary (indirect) costs reached 1.3–1.8 percent of Latvia’s GDP. Furthermore, non-financial costs from alcohol abuse represent a loss of nearly 90 thousand years spent in good health and with a good quality of life.

Furthermore, non-financial costs from alcohol abuse represent a loss of nearly 90 thousand years spent in good health and with a good quality of life. This stems primarily from the distress experienced by alcohol users’ household members, and the decline in life quality and premature mortality among users themselves.

Latvia stands out as a country with exceptionally high levels of absolute alcohol consumption per capita compared to other countries. Policy makers should implement effective preventive measures against alcohol consumption to maintain the sustainability of a healthy and productive society in Latvia.

Acknowledgement

This brief is based on a study Alcohol Use, its Consequences, and the Economic Benefits of Prevention Measures completed by BICEPS researchers in 2023, commissioned by the Health Ministry of Latvia (Pļuta et al., 2023).

References

Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

The Impact of Rising Gasoline Prices on Households in Sweden, Georgia, and Latvia – Is This Time Different?

20231201 The Impact of Rising Gasoline Prices Image 02

Over the last two years, the world has experienced a global energy crisis, with surging oil, coal, and natural gas prices. For European households, this translates into higher gasoline and diesel prices at the pump as well as increased electricity and heating costs. The increase in energy related costs began in 2021, as the world economy struggled with supply chain disruptions caused by the Covid-19 pandemic, and intensified as Russia launched a full-scale invasion of Ukraine in late February 2022. In response, European governments have implemented a variety of energy tax cuts (Sgaravatti et al., 2023), with a particular focus on reducing the consumer cost of transport fuel. This policy paper aims to contextualize current transport fuel prices in Europe by addressing two related questions: Are households today paying more for gasoline and diesel than in the past? And should policymakers respond by changing transport fuel tax rates? The analysis will focus on case studies from Sweden, Georgia, and Latvia, countries that vary in economic development, energy independence, reliance on Russian oil, transport infrastructure, and transport fuel tax rates. Through this study, we aim to paint a nuanced picture of the implications of rising fuel prices on household budgets and provide policy guidance.

Record High Gasoline Prices, Historically Cheap to Drive

Sweden has a long history of using excise taxes on transport fuel as a means to raise revenue for the government and to correct for environmental externalities. As early as in 1924, Sweden introduced an energy tax on gasoline. Later, in 1991, this tax was complemented by a carbon tax levied on the carbon content of transport fuels. On top of this, Sweden extended the coverage of its value-added tax (VAT) to include transport fuels in 1990. The VAT rate of 25 percent is applied to all components of the consumer price of gasoline: the production cost, producer margin, and excise taxes (energy and carbon taxes).

In May 2022, the Swedish government reduced the tax rate on transport fuels by 1.80 SEK per liter (0.16 EUR). This reduction was unprecedented. Since 1960, there have only been three instances of nominal tax rate reductions on gasoline in Sweden, each by marginal amounts in the range of 0.04 to 0.22 SEK per liter. Prior to the tax cut, the combined rate of the energy and carbon tax was 6.82 SEK per liter of gasoline. Adding the VAT that is applied on these taxes, amounting to 1.71 SEK, yields a total excise tax component of 8.53 SEK. This amount is fixed in the short run and does not vary with oil price changes.

Figure 1. Gasoline Pump Price, 2000-2023.

Source: Drivkraft Sverige (2023).

Figure 1 shows the monthly average real price of gasoline in Sweden from January 2000 to October 2023. The price has slowly increased over the last 20 years and has been historically high in the last year and a half. Going back even further, the price is higher today than at any point since 1960. Swedish households have thus lately been paying more for one liter of gasoline than ever before.

However, a narrow focus on the price at the pump does not take into consideration other factors that affect the cost of personal transportation for households.

First, the average fuel efficiency of the vehicle fleet has improved over time. New vehicles sold in Sweden today can drive 50 percent further on one liter of gasoline compared to new vehicles sold in 2000. Arguably, what consumers care about the most is not the cost of gasoline per se but the cost of driving a certain distance, as the utility one derives from a car is the distance one can travel. Accounting for vehicles’ fuel efficiency improvement over time, we find that even though it is still comparatively expensive to drive today, the current price level no longer constitutes a historical peak. In fact, the cost of driving 100 km was as high, or higher, in the 2000-2008 period (see Figure 2).

Figure 2. Gasoline Expenditure per 100 km.

Source: Trafikverket (2023) and Drivkraft Sverige (2023).

Second, any discussion of the cost of personal transportation for households should also factor in changes in household income over time. The Swedish average real hourly wage has increased by more than thirty percent between 2000-2023. As such, the cost of driving 100 km, measured as a share of household income, has steadily declined over time. Further, this pattern is consistent across the income distribution; for instance, the cost trajectory for the bottom decile is similar to that of all wage earners (as illustrated in Figure 3). In 1991, when the carbon tax was implemented, the average household had to spend around two thirds of an hour’s wage to drive 100 km. By 2020, that same household only had to spend one third of an hour’s wage to drive the same distance. There has been an increase in the cost of driving over the last two years, but in relation to income, it is still cheaper today to drive a certain distance compared to any year before 2013.

Figure 3. Cost of Driving as a Share of Income, 1991-2023.

Source: Statistics Sweden (2023).

Taken all together, we see that on the expenditure side, vehicles use fuel more efficiently over time and on the income side, households earn higher wages. Based on this, we can conclude that the cost of travelling a certain distance by car is not historically high today.

Response From Policymakers

It is, however, of little comfort for households to know that it was more expensive to drive their car – as a share of income – 10 or 20 years ago. We argue that what ultimately matters for households is the short run change in cost, and the speed of this change. If the cost rises too fast, households cannot adjust their expenditure pattern quickly enough and thus feel that the price increase is unaffordable. In fact, the change in the gasoline price at the pump has been unusually rapid over the last two years. Since the beginning of 2021, until the peak in June 2022, the (nominal) pump price rose by around 60 percent.

So, should policymakers respond to the rapid price increase by lowering gasoline taxes? The perhaps surprising answer is that lowering existing gasoline tax rates would be counter-productive in the medium and long run. Since excise taxes are fixed and do not vary with the oil price, they reduce the volatility of the pump price by cushioning fluctuations in the market price of crude oil. The total excise tax component including VAT constitutes more than half of the pump price in Sweden, a level that is similar across most European countries. This stands in stark contrast with the US, where excise taxes make up around 15 percent of the consumer price of gasoline. As a consequence, a doubling of the price of crude oil only increases the consumer price of gasoline in Sweden by around 35 percent, while it increases by about 80 percent in the US. Households across Sweden, Europe, and the US have adapted to the different levels of gasoline tax rates by purchasing vehicles with different levels of fuel efficiency. New light-duty vehicles sold in Europe are on average 45 percent more fuel-efficient compared to the same vehicle category sold in the US (IEA 2021). As such, US households do not necessarily benefit from lower gasoline taxation in terms of household expenditure on transport fuel. They are also more vulnerable to rapid increases in the price of crude oil. Having high gasoline tax rates thus reduces – rather than increases – the short run welfare impact on households. Hence, policymakers should resist the temptation to lower gasoline tax rates during the current energy crisis. With imposed tax cuts, households will, in the medium and long run, buy vehicles with higher fuel consumption and thus become more exposed to price surges in the future – again compelling policymakers to adjust tax rates, creating a downward spiral. Instead, alternative measures should be considered to alleviate the effects of the heavy price pressure on low-income households – for instance, revenue recycling of the carbon tax revenue and increased subsidies of public transport.

Conclusion

To reach environmental and climate goals, Sweden urgently needs to phase out the use of fossil fuels in the transport sector – Sweden’s largest source of carbon dioxide emissions. This is exactly what a gradual increase of the tax rate on gasoline and diesel would achieve. At the same time, it would benefit consumers by shielding them from the adverse effects of future oil price volatility.

The most common response from policymakers regarding fuel tax rates however goes in the opposite direction. In Sweden, the excise tax on gasoline and diesel was reduced by 1.80 SEK per liter in 2022 and the current government plans to further reduce the price by easing the biofuel mandate. Similar tax cuts have been implemented in a range of European countries. Therefore, the distinguishing factor in the current situation lies in the exceptional responses from policymakers, rather than in the gasoline costs that households are encountering.

Gasoline Price Swings and Their Consequences for Georgian Consumers

The energy crisis that begun in 2021 has also made its mark on Georgia, where the operational expenses of personal vehicles, encompassing not only gasoline costs but also maintenance expenses, account for more than 8 percent of the consumer price index. The rise in gasoline prices sparked public protest and certain opposition parties proposed an excise tax cut to mitigate the gasoline price surge. In Georgia, gasoline taxes include excise taxes and VAT. Until January 1, 2017, the excise tax was 250 GEL per ton (9 cents/liter), it has since increased to 500 GEL (18 cents/liter). Despite protests and the suggested excise tax reduction, the Georgian government chose not to implement any tax cuts. Instead, it initiated consultations with major oil importers to explore potential avenues for reducing the overall prices. Following this, the Georgian National Competition Agency (GNCA) launched an inquiry into the fuel market for motor vehicles, concluding a manipulation of retail prices for gasoline existed (Georgian National Competition Agency, 2023).

The objective of this part of the policy paper is to address two interconnected questions. Firstly, are Georgian households affected by gasoline price increases? And secondly, if they are, is there a need for government intervention to mitigate the negative impact on household budgets caused by the rise in gasoline prices?

The Gasoline Market in Georgia

Georgia’s heavy reliance on gasoline imports is a notable aspect of the country’s energy landscape. The country satisfies 100 percent of its gasoline needs with imports and 99 percent of the fuel imported is earmarked for the road vehicle transport sector. Although Georgia sources its gasoline from a diverse group of countries, with nearly twenty nations contributing to its annual gasoline imports, the supply predominantly originates from a select few markets: Bulgaria, Romania, and Russia. In the last decade, these markets have almost yearly accounted for over 80 percent of Georgia’s total gasoline imports. Furthermore, Russia’s share has substantially increased in recent years, amounting to almost 75 percent of all gasoline imports in 2023. The primary reason behind Russia’s increased dominance in Georgia’s gasoline imports is the competitive pricing of Russian gasoline, which between January and August in 2023 was almost 50 percent cheaper than Bulgarian gasoline and 35 percent cheaper than Romanian gasoline (National Statistics Office of Georgia, 2023). Given the dominance of Russian gasoline in Georgia, the end-user (retail) prices of gasoline in Georgia, are closer to gasoline prices in Russia than EU gasoline prices (see Figure 1).

Figure 1. End-user Gasoline Prices in Georgia, Russia and the EU, 2013-2022.

Source: International Energy Agency, 2023.

However, while the gasoline prices increased steadily in 2020-2022 in Russia, gasoline prices in Georgia increased sharply in the same period. This more closely replicated the EU price dynamics rather than the Russian one. The sharp price increase in gasoline raised concerns from the Georgian National Competition Agency (GNCA). According to the GNCA one possible reason behind the sharp increase in gasoline prices in Georgia could be anti-competitive behaviour among the five major companies within the gasoline market. Accordingly, the GNCA investigated the behaviour of major market players during the first eight months of 2022, finding violations of the Competition Law of Georgia. Although the companies had imported and were offering consumers different and significantly cheaper transport fuels compared to fuels of European origin, their retail pricing policies were identical and the differences in product costs were not properly reflected in the retail price level. GNCA claims the market players coordinated their actions, which could have led to increased gasoline prices in Georgia (National Competition Agency of Georgia. (2023).

Given that increased gasoline prices might lead to increased household expenditures for fuel, it is important to assess the potential impact of recent price developments on household’s budgets.

Exploring Gasoline Price Impacts

Using data from the Georgian Households Incomes and Expenditures Survey (National Statistics Office of Georgia, 2023), weekly household expenditures on gasoline and corresponding weekly incomes were computed. To evaluate the potential impact of rising gasoline prices on households, the ratio of household expenditures on gasoline to household income was used. The ratios were calculated for all households, grouped in three income groups (the bottom 10 percent, the top 10 percent and those in between), over the past decade (see Figure 2).

Figure 2. Expenditure on Gasoline as Share of Income for Different Income Groups in Georgia, 2013-2022.

Source: National Statistics Office of Georgia, 2023.

Figure 2 shows that between 2013 and 2022, average households allocated 9-14 percent of their weekly income to gasoline purchases. There is no discernible increase in the ratio following the energy crisis in 2021-2022.

Considering the different income groups, the upper 10 percent income group experienced a slightly greater impact from the recent rise in gasoline prices (the ratio increased), compared to the overall population. For the lower income group, which experienced a rise in the proportion of fuel costs relative to total income from 2016 to 2021, the rate declined between 2021 and 2022. Despite the decline in the ratio for the lower-level income group, it is noteworthy that the share of gasoline expenditure in the household budget has consistently been high throughout the decade, compared to the overall population and the higher-level income group.

The slightly greater impact from the rise in gasoline prices for the upper 10 percent income group is driven by a 4 percent increase in nominal disposable income, paired with an 8 percent decline in the quantity of gasoline (Figure 3) in response to the 22 percent gasoline price increase. Clearly, for this income group, the increase in disposable income was not enough to offset the increase in the price of gasoline, increasing the ratio as indicated above.

For the lower 10 percent income group, there was a 23 percent increase in nominal disposable income, paired with a 9 percent decline in the quantity of purchased gasoline (Figure 3) in response to the 22 percent gasoline price increase . Thus, for this group, the increase in disposable income weakened the potential negative impact of increased prices, eventually lowering the ratio.

Figure 3. Average Gasoline Quantities Purchased, by Household Groups, per Week (In Liters) 2013-2022.

Source: National Statistics Office of Georgia, 2023.

Conclusion

The Georgian energy market is currently fully dependent on imports, predominantly from Russia. While sharp increases in petrol prices have been observed during the last 2-3 years, they do not seem to have significantly impacted Georgian households’ demand for gasoline. Noteworthy, the lack of impact from gasoline price increases on Georgian households’ budgets, as seen in the calculated ratio (depicted in Figure 2), can be explained by the significant rise in Georgia’s imports from the cheap Russian market during the energy crisis years. Additionally, according to the Household Incomes and Expenditures survey, there was in 2022 an annual increase in disposable income for households that purchased gasoline. However, the data also show that low-income households spend a high proportion of their income on gasoline.

Although increased prices did not significantly affect Georgian households, the extremely high import dependency and the lack of import markets diversification poses a threat to Georgia’s energy security and general economic stability. Economic dependency on Russia is dangerous as Russia traditionally uses economic relations as a lever for putting political pressure on independent economies. Therefore, expanding trade and deepening economic ties with Russia should be seen as risky. Additionally, the Russian economy has, due to war and sanctions, already contracted by 2.1 percent in 2022 and further declines are expected (Commersant, 2023).

Prioritizing actions such as diversifying the import market to find relatively cheap suppliers (other than Russia), closely monitoring the domestic market to ensure that competition law is not violated and market players do not abuse their power, and embracing green, energy-efficient technologies can positively affect Georgia’s energy security and positively impact sustainable development more broadly.

Fueling Concerns: The True Cost of Transportation in Latvia

In May 2020, as the Latvian Covid-19 crisis began, Latvia’s gasoline price was 0.99 EUR per liter. By June 2022, amid the economic effects from Russia’s war on Ukraine, the price had soared to a record high 2.09 EUR per liter, sparking public and political debate on the fairness of fuel prices and potential policy actions.

While gas station prices are salient, there are several other more hidden factors that affect the real cost of transportation in Latvia. This part of the policy paper sheds light on such costs by looking at some of its key indicators. First, we consider the historical price of transport fuel in Latvia. Second, we consider the cost of fuel in relationship to average wages and the fuel type composition of the vehicle fleet in Latvia.

The Price of Fuel in Latvia

Latvia’s nominal retail prices for gasoline (green line) and diesel (orange line) largely mirror each other, though gasoline prices are slightly higher, in part due to a higher excise duty (see  Figure 1). These local fuel prices closely follow the international oil market prices, as illustrated by the grey line representing nominal Brent oil prices per barrel.

The excise duty rate has been relatively stable in the past,  demonstrating that it has not been a major factor in fuel price swings. A potential reduction to the EU required minimum excise duty level will likely have a limited effect on retail prices. Back of the envelope calculations show that lowering the diesel excise duty from the current 0.414 EUR per liter to EU’s minimum requirement of 0.33 EUR per liter could result in approximately a 5 percent drop in retail prices (currently, 1.71 EUR per liter). This at the cost of a budget income reduction of 0.6 percent, arguably a costly policy choice.

In response to recent years’ price increase, the Latvian government opted to temporarily relax environmental restrictions, making the addition of a bio component to diesel and gasoline (0.065 and 0.095 liters per 1 liter respectively) non-mandatory for fuel retailers between 1st of June 2022 until the end of 2023. The expectation was that this measure would lead to a reduction in retail prices by approximately 10 eurocents. To this date, we are unaware of any publicly available statistical analysis that verifies whether the relaxed restriction have had the anticipated effect.

Figure 1. Nominal Retail Fuel Prices and Excise Duties for Gasoline and Diesel in Latvia (in EUR/Liter), and Nominal Brent Crude Oil Prices (in EUR/Barrel), January 2005 to August 2023.

Source: The Central Statistical Bureau of Latvia, St. Louis Federal Reserve’s database, OFX Monthly Average Rates database, The Ministry of Finance of Latvia, The State Revenue Service of Latvia.

The True Cost of Transportation

Comparing fuel retail prices to average net monthly earnings gives insight about the true cost of transportation in terms of purchasing power. Figure 2 displays the nominal net monthly average wage in Latvia from January 2005 to June 2023 (grey line). During this time period the average worker saw a five-fold nominal wage increase, from 228 EUR to 1128 EUR monthly. The real growth was two-fold, i.e., the inflation adjusted June 2023 wage, in 2005 prices, was 525 EUR.

Considering fuel’s share of the wages; one liter of gasoline amounted to 0.3 percent of an average monthly wage in 2005, as compared to 0.12 percent in 2023, with diesel displaying a similar pattern. Thus, despite recent years’ fuel price increase, the two-fold increase in purchasing power during the same time period implies that current fuel prices may not be as alarming for Latvian households as they initially appeared to be.

Figure 2. Average Nominal Monthly Net Wages in Latvia and Nominal Prices of One Liter of Gasoline and Diesel as Shares of Such Wages (in EUR), January 2005 to June 2023.

Source: The Central Statistical Bureau of Latvia.

Another factor to consider is the impact of technological advancements on fuel efficiency over time. The idea is simple: due to technological improvements to combustion engines, the amount of fuel required to drive 100 kilometers has decreased over time, which translates to a lower cost for traveling additional kilometers today. An EU average indicator shows that the fuel efficiency of newly sold cars improved from 7 liters to 6 liters per 100 km, respectively, in 2005 and 2019. While we lack precise data on the average fuel efficiency of all private vehicles in Latvia, we can make an informed argument in relation to the technological advancement claim by examining proxy indicators such as the type of fuel used and the average age of vehicles.

Figure 3 shows a notable change in the fuel type composition of the vehicle fleet in Latvia. Note that the decrease in the number of cars in 2011 is mainly due to a statistical correction for unused cars. At the start of the 21st century, 92 percent of Latvian vehicles were gasoline-powered and 8 percent were diesel-powered. By 2023, these proportions had shifted to 28 percent for gasoline and 68 percent for diesel. Diesel engines are more fuel efficient, usually consuming 20-35 percent less fuel than gasoline engines when travelling the same distance. Although diesel engines are generally pricier than their gasoline counterparts, they offer a cost advantage for every kilometer driven, easing the impact of rising fuel prices. A notable drawback of diesel engines however, is their lower environmental efficiency – highlighted following the 2015 emission scandal. In part due to the scandal, the diesel vehicles growth rate have dropped over the past five years in Latvia.

Figure 3. Number of Private Vehicles by Fuel Type and the Average Age of Private Vehicles in Latvia, 2001 to 2023.

Source: The Central Statistical Bureau of Latvia, Latvia’s Road Traffic Safety Directorate.

Figure 3 also shows that Latvia’s average vehicle age increased from 14 years in 2011 to 15.1 years in 2023. This is similar to the overall EU trend, although EU cars are around 12 years old, on average. This means that, in Latvia, the average car in 2011 and 2023 were manufactured in 1997 and 2008, respectively. One would expect that engines from 2008 have better technical characteristics compared to those from 1997. Recent economic research show that prior to 2005, improvements in fuel efficiency for new cars sold in the EU was largely counterbalanced by increased engine power, enhanced consumer amenities and improved acceleration performance (Hu and Chen, 2016). I.e.,  cars became heavier, larger, and more powerful, leading to higher fuel consumption. However, after 2005, cars’ net fuel efficiency started to improve. As sold cars in Latvia are typically 10-12 year old vehicles from Western European countries, Latvia will gradually absorb a more fuel-efficient vehicle fleet.

Conclusion

The increase of purchasing power, a shift to more efficient fuel types and improvements in engine efficiency have all contributed to a reduction of the overall real cost of transportation over time in Latvia. The recent rise in fuel prices to historically high levels is thus less concerning than it initially appears. Moreover, a growing share of cars will not be directly affected by fuel price fluctuations in the future. Modern electric vehicles constitute only 0.5 percent of all cars in Latvia today, however, they so far account for 10 percent of all newly registered cars in 2023, with an upward sloping trend.

Still, politicians are often concerned about the unequal effects of fuel price fluctuations on individuals. Different car owners experience varied effects, especially when considering factors like income and location, influencing transportation supply and demand.

First, Latvia ranks as one of the EU’s least motorized countries, only ahead of Romania, with 404 cars per 1000 inhabitants in 2021. This lower rate of vehicle ownership is likely influenced by the country’s relatively low GDP per capita (73 percent of the EU average in 2022) and a high population concentration in its capital city, Riga (32 of the population lives in Riga city and 46 percent in the Riga metropolitcan area). In Riga, a developed public transport system reduces the necessity for personal vehicles. Conversely, areas with limited public transport options, such as rural and smaller urban areas, exhibit a higher demand for personal transportation as there are no substitution options and the average distance travelled is higher than in urban areas. Thus, car owners in these areas tend to be more susceptible to the impact of fuel price volatility.

Second, Latvia has a high Gini coefficient compared to other EU countries, indicating significant income inequality (note that the Gini coefficient measures income inequality within a population, with 0 representing perfect equality and 1 indicating maximum inequality. In 2022, the EU average was 29.6 while Latvia’s Gini coefficient was 34.3, the third highest in the EU). With disparities in purchasing power, price hikes tend to disproportionately burden those with lower incomes, making fuel more costly relative to their monthly wages.

These income and location factors suggest that inhabitants in rural areas are likely the most affected by recent price hikes. Distributional effects across geography (rural vs urban) are often neglected in public discourse, as the income dimension is more visible. But both geography and income factors should be accounted for in a prioritized state support, should such be deemed necessary.

References

Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

Employment and Envelope Wages During the Covid-19 Crisis in Latvia

20231113 Envelope Wages Tax Evasion Image 01

The Covid-19 pandemic created one of the most substantial negative exogenous shocks in decades, forcing firms to rapidly adapt. This brief examines an adjustment mechanism that played a significant role in Latvia, and potentially in other countries in Eastern and Central Europe. Specifically, we focus on the role of envelope wages as a buffer for absorbing the shock. Our analysis demonstrates that this form of tax evasion indeed acted as a cushion during the Covid-19 pandemic. Our results indicate that, in the short run, tax-evading firms experienced smaller employment losses in response to the Covid-19 shock compared to compliant firms.

Introduction

The Covid-19 pandemic generated one of the largest negative, exogenous shocks in decades. To absorb this shock, firms had to swiftly adapt. Prior literature has demonstrated that firms responded by reducing employment and investment (Lastauskas, 2022; Fernández-Cerezo et al., 2023; Buchheim et al., 2020). In this brief, we discuss another margin of adjustment – potentially important for many countries in the region. We focus on the role of envelope wages as a buffer for negative shock absorption.

Envelope wages is a widespread form tax evasion, in which, for employees that are formally registered, a portion of their salary (often at the minimum wage level) is reported to tax authorities, while the remaining ‘envelope’ portion is paid unofficially. The prevalence of this phenomenon has been extensively documented in Eastern and Central Europe (see Kukk and Staehr (2014) and Paulus (2015) for Estonia, Gorodnichenko et al. (2009) for Russia, Putniņš and Sauka (2015) for the Baltic States, Tonin (2011) and Bíró et al. (2022) for Hungary).

In addition to the evident objective of reducing tax obligations, a primary incentive for firms to employ this evasion scheme is the extra flexibility it provides. The unreported portion of wages operates outside of the legal framework, offering firms a means of adaptation in the face of production restrictions, supply chain disruptions, and overall substantial uncertainty caused by the Covid-19 pandemic. In this brief, we argue that firms utilizing envelope wages reduced their employment less than compliant firms during the pandemic in Latvia.

Identifying Firms That Pay Envelope Wages

We identify firms that paid (at least partly) their employees in cash before the pandemic using a rich combination of Latvian administrative and survey data and the methodology proposed by Gavoille and Zasova (2021).

The idea is as follows: We use a subsample of firms for which we can assume that we know whether they pay envelope wages and, using this subsample, train an algorithm that is capable of distinguishing compliant and evading firms based on their observed characteristics and reported financials.

Following Gavoille and Zasova (2021), we use firms owned by Nordic investors as a subsample of tax-compliant firms. To obtain a subsample of non-compliant firms, we combine data on administrative (i.e., reported) wages with several rounds of Labor Force Survey data in order to spot employees who are paid suspiciously little given their personal characteristics (education, experience, etc). Firms employing these employees form the subsample of evading firms. Using these samples of compliant and evading firms, we train a Random Forest algorithm to classify firms according to their type. We then use the algorithm to classify the universe of firms used in this study. Table 1 shows the classification results.

Table 1. Classification results: share of tax-evading firms and employees.

Source: Authors’ calculations.

We find that almost 40 percent of firms (employing about 20 percent of employees) underreport at least some of their workers’ wages. The cross-sectoral heterogeneity is consistent with survey evidence: the construction and transport sectors are the sectors with the highest prevalence of envelope payments. Comparing the share of tax-evading firms with the share of workers working within these firms also indicates that on average, tax-evading firms are smaller than tax-compliant ones. This is yet again in accordance with survey evidence.

Employment Response During Covid-19

Figure 1. Average firm-level change in employment during the Covid-19 pandemic.

Note: This figure shows the average change in employment between January 2020 and any subsequent month, weighted by firm size (average turnover 2017-2019).
Source: Authors’ calculations.

The Covid-19 crisis had a severe impact on Latvia. The government declared a state of emergency as early as March 13, 2020, which entailed significant restrictions on gatherings and on-site work, leading to a six-fold increase in the proportion of remote workers within a matter of months.

During the second wave, in Autumn 2021, Latvia had the highest ranking in the world in terms of new daily positive cases per capita. A substantial number of firms were directly affected by the pandemic (see Figure 1).

We study firm-level employment response at a monthly frequency in compliant and tax-evading firms, from January 2020 to December 2021. Our empirical approach is in the spirit of Machin et al. (2003) and Harasztosi and Lindner (2019), who study the effect of minimum wage shocks. In essence, this approach consists of a series of cross-section regressions, where the dependent variable is the percentage change in employment in a firm between a reference period (set to January 2020) and any subsequent month until December 2021. Our key interest is the difference in cumulative employment response between tax-compliant and evading firms, controlling for a set of (pre-pandemic) firm characteristics, such as the firm’s age, average profitability, average export share, and average labor share over the 2017-2019 period.

The Aggregate Effect

Figure 2 shows the estimated coefficients that measure the difference between employment effects in compliant and tax-evading firms, aggregate for all sectors. Period 0 denotes our reference period, i.e., January 2020, while the estimated coefficients in other periods show the cumulated difference between tax compliant and tax-evading firms in the respective period relative to January 2020 (e.g., the estimated coefficient in period 10 shows the cumulated differential employment response in October 2020 vis-à-vis January 2020).

We document a noticeable difference in the employment response between the two types of firms starting in April 2020. The positive coefficient associated with evading firms indicates that the change in employment growth was not as negative in evading firms as in compliant firms (see Figure 2). Labor tax-evading firms exhibit, on average, a less sensitive employment response than tax-compliant firms. In March 2021, the point estimates are about 0.025, implying that compared to March 2020, tax-evading firms contracted, on average, 2.5 percentage points less than compliant ones. This difference however fades over time and turns insignificant (at the 95 percent level) about halfway through 2021.

Figure 2. Evasion and total employment.

Note: This figure shows the cumulative difference between employment effects in compliant and tax-evading firms, aggregate for all sectors, by month, with respect to January 2020 (reference period).
Source: Authors’ calculations.

Differences by Sector

Figure 3 displays the estimated difference in employment response, disaggregating the sample by sector. We show the results for two sectors: trade and transportation. These two sectors exhibited the most significant differences in employment response between evading and non-evading firms.

For trade, evading firms have been able to maintain employment losses at approximately 5 percentage points less than compliant firms (see Figure 3(a)). This is consistent with the envelope wage margin mechanism. Contrary to the aggregate results, the difference in employment response does not fade over time. This suggests that this margin is not a shock absorber only in the very short run.

The decrease of the evader effect at the aggregate level is caused by negative point estimates of the evasion indicator in the transportation sector, starting in the first quarter of 2021 (see Figure 3(b)). In this sector, evading firms have on average experienced a larger employment decline in 2021 than compliant firms.

Figure 3. Employment effect – by sector.

Note: These figures show the cumulative difference between employment effects in compliant and tax-evading firms, disaggregated by sectors. Source: Authors’ calculations.

The outcome in the transportation sector is likely influenced by the taxi market. There were two major changes in 2021 that particularly affected taxi drivers receiving a portion of their remuneration through envelopes. Firstly, amendments to State Revenues Service’s (SRS) regulations made it more difficult to underreport the number of taxi trips, as each ride was now automatically recorded in the SRS system through taxi apps. Secondly, commencing in July, legal amendments mandated a minimum social security tax, which had to be paid based on at least the minimum wage. Given that many taxi drivers work part-time, and that those associated with evading firms tend to underreport their rides, this new requirement was more binding for evading firms. Additionally, there was a significant shift of taxi drivers to the food delivery sector, where demand for driver services surged during the pandemic.

Conclusion

Our results indicate that employment losses in response to the Covid-19 shock were smaller in tax-evading firms than in compliant firms in the short run. We also demonstrate that by the end of 2021, the discrepancy between the two types of firms had disappeared. This can be explained by significant heterogeneity in employment responses across sectors.

These findings contribute to our understanding of the pandemic’s impact on the size of the informal sector. Despite tax-evading firms generally having more restricted access to finance, the added flexibility provided by unreported wages may have increased their resilience to the negative shock.

Acknowledgement

This brief is based on a forthcoming working paper COVID-19 Crisis, Employment, and the Envelope Wage Margin. The authors gratefully acknowledge funding from EEA and Norway, grant project “Micro-level responses to socio-economic challenges in face of global uncertainties” (Grant No. S-BMT-21-8 (LT08-2-LMT-K-01-073)).

References

Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes. 

Choosing Latvia: Understanding the Decision-Making Factors of Displaced Ukrainians

20220317 Ukrainian Refugees in Poland Image 03

This policy brief is based on an empirical examination of the early-stage migration of Ukrainian war asylum seekers to Latvia in 2022, following the Russian invasion. The study highlights the urgent nature of their displacement and identifies the pivotal role of kinship in Latvia in the decision-making. Three categories of refugees emerge based on kinship ties, employment opportunities, and cultural affinity. The study also reveals the substantial influence of the pre-existing Ukrainian diaspora and underlines the significance of network effects in refugees’ location decisions. Contrary to previous studies, refugees didn’t necessarily settle for the first country available. The research underscores the strategy of seeking support from personal networks in acute displacement scenarios, which appears to be the most influential factor for the choice of location in the decision-making process.

Ukrainian Displaced People in Latvia

The Russian invasion of Ukraine in 2022 triggered a geopolitical upheaval in Europe and resulted in a mass exodus that had not been witnessed since World War II. With the war showing no signs of cessation, return for many of these displaced people appears difficult in the near future. Latvia, although not a bordering country, have become a haven for 36 000 Ukrainian refugees.

This brief seeks insight into Ukrainian displaced people’s preference for Latvia, using interviews conducted in March 2022, a month after the war began. With no common border between Ukraine and Latvia these refugees had to transit through other countries, making the question about the choice of Latvia as their ultimate destination particularly relevant.

Unlike during the migration crisis in 2015 and during the recent influx of Syrians and other groups, the Ukrainian refugees found themselves being welcomed with open arms, belying Latvia’s typically guarded stance towards immigrants. This unexpected warmth is influenced by a multifaceted kinship rooted in historical connections from the Soviet era, a pre-existing Ukrainian diaspora in Latvia, labor migration, and shared cultural elements.

These factors can also play a role in Ukrainian refugees’ choice of Latvia as their ultimate destination. The study underlying this policy brief seeks to explore these facets and unravel the reasons behind the Ukrainian refugees’ choice to seek safety in Latvia.

Migration Decisions

Two aspects are crucial in the analysis of migration decisions: the factors that influence refugees’ choice of destination and the process underlying this decision.

Traditional assumptions surrounding asylum-seeker migration, as emphasized by Böcker and Havinga (1997), suggest that when people are forced to flee, their primary focus is safety – not destination. However, more nuanced perspectives have evolved in recent studies (see Robinson and Sergott, 2002; Brekke and Aarset, 2009). They highlight the calculated and adaptable nature of refugee destination choices throughout the asylum-seeking migration journey, demonstrating that circumstances and journey stage significantly influence destination choices.

Research indicates that host country policies and economic conditions can both enhance and limit refugee flows (Czaika and de Haas, 2017; Ortega and Peri, 2013; Brekke and Aarset, 2009; Diop-Christensen and Diop, 2021; Kang, 2021; Suzuki,2020; Collyer, 2005). However, another line of research emphasizes that policy and economic factors are secondary to networks, cultural affinity, language, and perceptions in determining destination choices (Robinson and Sergott, 2002). Factors such as social networks (Koser and Pinkerton, 2002; Tucker 2018), kinship (Havinga and Böcker, 1999; Neumayer, 2005; Mallett and Hagen-Zanker, 2018), financial resources (Mallett and Hagen-Zanker, 2018), geography (Neumayer, 2005; Kang, 2021), destination country image (Benzer and Zetter, 2014), culture (Suzuki, 2020), and colonial links (Havinga and Böcker, 1999) have been established to be significant at various stages of migration. Economic and education opportunities are also found to have a marginal influence on destination decision-making compared to the possibility of resolving statelessness (Tucker, 2018).

These varying determinants of destination may also be contingent on the refugee journey stage. Policies may not dominate in acute cases of forced migration (Diop-Christensen and Diop, 2021). For individuals with time to prepare for migration, a cost-benefit analysis often informs their decisions. In contrast, those in urgent circumstances, such as during the Russian invasion of Ukraine, may have to take immediate refuge and put less emphasis on benefits and policies (Robinson and Sergott, 2002). Destination determinants differ by both origin and destination countries (Havinga and Böcker, 1999, Tucker, 2018, Gilbert and Koser, 2006). Thus, research on underexplored regions and countries is valuable for a comprehensive understanding of migration patterns.

Migration, voluntary or forced, involves intricate decision-making. As Mallett and Hagen-Zanker (2018) aptly state, the dynamic experiences ‘on the road’ shape refugees’ journey and destination choices. Robinson and Sergott (2002) and Brekke and Aarset, 2009 have pioneered models for asylum seekers’ decision-making, suggesting that factors such as networks, language, cultural affinity, and perceptions evolve across different stages of the asylum journey. Others, like Gonsalves (1992) and Shultz et al. (2020), have constructed models delineating stages of refugee passage and displacement, highlighting the changing needs and preferences of refugees.

While existing literature mainly focuses on the later stages of forced migration journeys, limited empirical evidence exists on the migration moves during acute displacement. Additionally, further understanding on migration induced by the war on Ukraine is needed. There is also incomplete coverage of asylum seeker and refugee topics in the Baltic countries, making such research particularly relevant. To address these gaps, this brief aims to provide qualitative findings on the decision-making and experiences of Ukrainian displaced people in Latvia.

Understanding the Decision

The research underlying this brief explored the reasons behind Ukrainian displaced people’s choice of Latvia as their migration destination during the early part of the invasion. The study is based on 34 semi-structured, in-depth interviews with displaced people conducted in March 2022. The dataset is part of a larger study that includes continuous interviews to understand Ukrainian displaced people’s lives, plans and needs in Latvia.

From the interviews, it was apparent that the predominant factor in respondents’ decision-making was the presence of kin or acquaintances in Latvia.

All but one participant had some connection to Latvia, whether through distant relatives, friends, or professional contacts. The one participant without such connections arrived from Russia and not from Ukraine, working on a contract. A minority of our participants considered staying in Ukraine. One example is Lidiia, who initially planned to move near Lviv, but redirected to Riga during the journey.

“She found a family that would host us, 100 km from Lviv… We agreed, but then our friends… called us on the way, we were leaving Kyiv under bombardment. Our train was delayed because of the air alarm. When we just arrived there, a shell exploded above the railway station… And on the way, friends from Riga called us and invited us: ‘Come, everyone will help here’. Therefore, everything changed while we were on the train, we decided everything“ (Lidiia).

Proximity of kin was not the primary concern for the interviewees; the mere fact that they had a relative in Latvia appeared more influential in their narratives. Indeed, the majority of participants had distant rather than close kin, though a few had close family in Latvia (grandparents, parents, common-law husband, and sister). As Olena explained, the presence of even distant relatives influenced her choice: “there are distant relatives, very distant… That’s why we came” (Olena). However, ties in Latvia were not the only determinants as many of the participants also had family connections in other parts of Europe.

The speed of decision-making was also striking – most decisions to migrate were not a matter of long-term planning but a reaction to the sudden crisis, often influenced by incoming offers of assistance. Nataliia remembered: “My mother said, ‘You have to leave because everything is so fatally bad. Take the children and leave.’ And literally overnight I packed up, bought the tickets. But first I went to Poland, to my brother” (Nataliia).

Maryana ended up choosing her destination only after leaving home. “At first, we thought to go to Poland, but it is completely crowded, and then we called to whoever we could. There are no relatives in other countries. No, there are relatives in other cities, but these are Luhansk, Donetsk, we are from Slobozhanska Ukraine, so all our relatives are from the side where very heavy fighting is going on now“ (Maryana). Such testimonies illuminate how, owing to the immediacy of the situation, the eventual destination of some displaced Ukrainians was not predetermined but evolved during their respective journeys.

From the interviews with the participants who knew someone in Latvia, one can identify three groups based on the main factor that determined their decision.

Network, First of All

For respondents who did not have family in Latvia, friends, acquaintances, and professional contacts in Latvia acted as anchors. Like family members, such acquaintances often reached out, offering assistance and lodging as soon as they heard the news of the war. The influx of supportive communication from Latvian acquaintances influenced the decision for many participants.

Olha decided to flee with her friend, who had a distant cousin residing in Latvia. Upon the onset of the conflict, the cousin reached out and urged them to come to Latvia. As Olha recalls: “As soon as she heard that there was a bombing in Kharkiv, she said, ‘Come’. My friend, with whom I came, Lesya, does not have a car, so she immediately told me… let’s run away’” (Olha).

Lidiia received an invitation from a Latvian friend she had met through her church, even as she was already in the process of fleeing Ukraine. Similarly, Andrii, who was vacationing abroad at the time of the war’s outbreak, remembered: “On the 25th our best friend wrote to us that, ‘There is housing, come here’ and we began to negotiate with the embassy to fly here” (Andrii).

Even in the absence of explicit messages, displaced individuals recalled having friends and family in Latvia and chose to make their way to Riga. Olena, like Lidiia, initially set off without a clear destination in mind. It wasn’t until she reached the border that she decided to head to Latvia: “Just at the border that you decided where to go?” (Olena).

Existing friendships and ongoing communication also influenced some people’s choice to opt for Latvia. Olha (2) was encouraged by her daughter to relocate to Riga due to her daughter’s friendships with Latvians that she had formed at a camp in Estonia: “Friends appeared, with whom she was in close contact for six months. That’s why for her there was no choice at all ‘Where?’. She immediately said: ‘To Riga’” (Olha (2)).

Opportunities and Realities

The turning point for many respondents was their arrival in Poland as, initially, Latvia was not the principal or only choice of destination. These respondents emphasized that, besides having friends and relatives in Latvia, they also contemplated where they might find better opportunities. Their narratives provide a contrasting perspective of Poland and Latvia. While traversing Poland, their general impression was that the country was already ‘overfilled’, which in turn kindled the notion that Latvia might harbor more possibilities. For this group of displaced individuals, the importance of employment prospects was paramount.

Nataliia took the decision to head for Latvia, choosing to stay with remote kin there rather than with her sibling in Poland, as she believed Poland lacked opportunities for her. In Myroslava’s case, a friend helped secure a job in Latvia: “We didn’t choose Latvia for any particular reason – better or worse, we didn’t care. We needed somewhere to stay, somewhere to work in order to live. Well, that’s why when a job turned up through acquaintances, they said that a person was needed here, we immediately gathered. Could not be found in Poland. In Poland, there was simply no work, no housing” (Myroslava).

Bohdan, too, mentioned the crowdedness and the high cost of living in Poland, hence deciding to move further north to Latvia: “We didn’t have a specific plan because we weren’t at all sure we would succeed. In general, my wife benefits from going to Poland, she works for an IT company operating in Poland. And we thought about getting there at first, but when we got to Poland, everything was already full. There were such expensive options, $1600 a month, we were shocked” (Bohdan).

Anastasiia echoed similar concerns: “We arrived in Warsaw, reunited there and tried to stay in Warsaw and look for a place, but there are a lot of people there, and there is no place to live, very… food, maybe cheaper than in Latvia, but there is no place to live… no place to work. And I would like to work somehow… not to be dependent” (Anastasiia).

These stories illuminate another stratum of decision-making, that beyond familial ties, participants also considered the opportunities available at their chosen destination. They accumulate information on their journey and recalibrate their destination accordingly.

Cultural Kinship, Language, Diaspora

Not all participants had prior personal experience with Latvia, even if they had relatives there. A lot of their understanding about the country stemmed from stories they’d heard or news they’d come across. This third group of participants decided on Latvia not only because they knew someone in the country, but also because they saw value in shared language, culture, and history.

Political and cultural connections played a significant role in their choice. Being able to communicate in Russian and Ukrainian in Latvia was a crucial factor, as it was associated with a smoother integration process and increased job opportunities. Nadiia, who traveled to Latvia via Poland and Budapest, elaborated on this: “And I was in Latvia and here there is an opportunity to communicate in Ukrainian, in Russian” (Nadiia).

The possibility of being accepted and integrated into the local community was also mentioned as a decision-driver. Oksana shared that her father, who had previously worked in Riga, advised her to go to Latvia: “you guys, probably go to Riga, well, because you will be accepted there, accommodated” (Oksana).

Nonetheless, choosing Latvia because of the possibility to communicate in Russian does not come without complications. Nataliia B., for instance, found the topic of language stirring up strong emotions and confessed that she doesn’t wish to speak Russian anymore: “I had such a psychological reaction – I didn’t speak Ukrainian for many years, and when all these events began, I read, I remember well how I woke up in the morning and began to speak Ukrainian. My thoughts have become Ukrainian” (Nataliia B.).

Moreover, having knowledge of the Ukrainian diaspora in the country also proved an important factor. “I also found out that there is a Ukrainian diaspora in Latvia of about 50 000 people, as I heard in the Latvian news. And this also encouraged me, I realised that I could find help from my compatriots” (Nadiia). This observation underlines the role of cultural kinship in the decision-making process regarding destination, and it can indeed be seen as a decisive factor. As the diaspora expands with the influx of more displaced people, this rationale for choosing Latvia may become increasingly common.

Conclusion

The study underlying this brief provided empirical insight into the initial phases of Ukrainian war asylum seekers’ journey to Latvia in 2022, enhancing our understanding of the factors that influenced the choice of Latvia over other destinations.

Ukrainians fleeing the early stage of the 2022 Russian invasion were compelled to make swift and difficult decisions due to the pressing crisis. Leaving behind their familiar lives, properties, and dear ones – often the very individuals facilitating their exodus for safety reasons – was a harrowing reality. The support from kin and acquaintances in Latvia was crucial in endorsing their decision to seek refuge in the country.

Three groups emerged among the Ukrainian refugees in Latvia, all connected by personal relationships to some degree. The factors influencing their migration ranged from the presence of kin and considerations of employment prospects, to shared language, culture, and history. The fact that the initial outreach usually originated from the Latvian side underscores the profound solidarity and active support provided by Latvians to their Ukrainian counterparts. This likely also played a significant role in the refugees’ decisions. The pre-existing Ukrainian diaspora in Latvia, estimated at around 50 000 before the invasion, also significantly influenced the choice of Latvia as a refuge.

Financially-related factors such as seeking benefits were largely absent from the narratives, likely due to the geographic proximity, relatively low costs, and the urgent nature of the displacement. The most significant determinant in choosing Latvia as the destination appeared to be the network effect, contrasting with Robinson and Sergott (2002) findings that acute asylum seekers often settle for the first country available.

Given the emergency nature of the displacement, no unambiguous pattern in the location decision could be established. The narrative varied considerably among respondents with decisions often being made, or altered, on the fly. However, in most cases, personal relationships played a primary role in shaping the choices among Ukrainian refugees in Latvia.

For policy-makers planning and responding to acute migration crises, the study highlights the importance of mapping and understanding multifaceted kinships, as well as culture and history. The mapping can be used to plan support and allocate resources to give displaced people an opportunity of a place where they feel welcomed and connected, with hopes of greater integration.

References

  • Böcker, A. and Havinga, T. (1997). Asylum Migration to the European Union: Patterns of Origin and Destination, Luxembourg: Office for Official Publications of the European Communities.
  • Brekke, J. P. and Aarset, M. F. (2009). Why Norway? Understanding Asylum Destinations, Institute for Social Research, Oslo.
  • Collyer, M. (2005). When do social networks fail to explain migration? Accounting for the movement of Algerian asylum-seekers to the UK. Journal of Ethnic and Migration Studies, 31(4), 699-718.
  • Czaika, M. and de Haas, H. (2017). The effect of visas on migration processes. International Migration Review, 51(4), 893-926.
  • Diop-Christensen, A. and Diop, L. E. (2021). What do asylum seekers prioritise—safety or welfare benefits? The influence of policies on asylum flows to the EU15 countries. Journal of Refugee Studies.
  • Gilbert, A. and Koser, K. (2006). Coming to the UK: what do asylum-seekers know about the UK before arrival? Journal of ethnic and migration studies, 32(7), 1209-1225.
  • Gonsalves, C. J. (1992). Psychological stages of the refugee process: A model for therapeutic interventions. Professional Psychology: Research and Practice, 23(5), 382.
  • Havinga, T. and Böcker, A. (1999). Country of asylum by choice or by chance: Asylum‐seekers in Belgium, the Netherlands and the UK. Journal of ethnic and migration studies, 25(1), 43-61.
  • Kang, Y. D. (2021). Refugee crisis in Europe: determinants of asylum seeking in European countries from 2008–2014. Journal of European Integration, 43(1), 33-48.
  • Koser, K. and Pinkerton, C. (2002). The social networks of asylum seekers and the dissemination of information about countries of asylum.
  • Mallett, R., & Hagen-Zanker, J. (2018). Forced migration trajectories: An analysis of journey-and decision-making among Eritrean and Syrian arrivals to Europe. Migration and Development, 7(3), 341-351.
  • Neumayer, E. (2005). Bogus refugees? The determinants of asylum migration to Western Europe. International studies quarterly, 49(3), 389-409.
  • Neumayer, E. (2004). Asylum destination choice: what makes some West European countries more attractive than others? European Union Politics, 5(2), 155-180.
  • Ortega, F., and Peri, G. (2013). The effect of income and immigration policies on international migration. Migration Studies, 1(1), 47-74.
  • Robinson, V., and Segrott, J. (2002). Understanding the decision-making of asylum seekers (Vol. 12). London: Home Office.
  • Shultz, C., Barrios, A., Krasnikov, A. V., Becker, I., Bennett, A. M., Emile, R., Hokkinen, M., Pennington, J. R., Santos, M., and Sierra, J. (2020). The Global Refugee Crisis: Pathway for a More Humanitarian Solution. Journal of Macromarketing, 40(1), 128–143.
  • Suzuki, T. (2020). Destination choice of asylum applicants in Europe from three conflict-affected countries. Migration and Development, 1-13.
  • Tucker, J. (2018). Why here? Factors influencing Palestinian refugees from Syria in choosing Germany or Sweden as asylum destinations. Comparative migration studies, 6(1), 1-17.

Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

Personality Traits, Remote Work and Productivity

20221024 Personality Traits, Remote Work Image 01

The Covid-19 pandemic generated a massive and sudden shift towards teleworking. Survey evidence suggests that remote work will stick in the post-pandemic period. The effects of remote work on workers’ productivity are however not well understood, some workers gaining in productivity whereas others experience the opposite. How can this large heterogeneity in workers productivity following the switch to teleworking be explained? In this brief, we discuss the importance of personality traits. We document strong links between personality, productivity, and willingness to work from home in the post-pandemic period. Our results suggest that a one-size-fits-all policy regarding remote work is unlikely to maximize firms’ productivity.

Introduction

The Covid-19 pandemic triggered a large and sudden exogenous shift towards working from home (WFH). Within a few months in Spring 2020, the share of remote workers increased from 8.2 percent to 35.2 percent in the US (Bick et al., 2020), and from 5 percent to more than 30 percent in the EU (Sostero et al., 2020). Surveys of business leaders suggest that WFH will stick in the post-pandemic period (e.g., Bartik et al., 2020).

The prevalence of teleworking will ultimately depend on its impact on workers’ productivity and well-being. This impact however remains ambiguous, some studies reporting an overall positive impact, some studies a negative one. Overall, the balance of these pros and cons can vary greatly across individuals. The existing literature emphasizes the importance of gender and occupation for workers’ productivity under WFH arrangements, but a large share of this heterogeneity remains unexplained.

In a recent paper (Gavoille and Hazans, 2022) we investigate the link between personality traits and workers’ productivity when working from home. Importance of non-cognitive skills, in particular personality traits, for individual labor market outcomes is well documented in the literature (e.g., Heckman et al., 2006; Heckman and Kautz, 2012). In the context of WFH, soft skills such as conscientiousness or emotional stability, are good candidates for explaining heterogeneity in relative productivity at the individual employee level.

The Latvian context provides an ideal setup for studying the effect of teleworking on productivity. First, Latvia has a large but unexploited potential for teleworking. Dingel and Neiman (2021) estimate that 35 percent of Latvian jobs could be done remotely, which is about the EU average. However, prior to the pandemic only 3 percent of the workforce was working remotely – one of the smallest figures in the EU. Second, the Latvian government declared a state of emergency in March 2020, which introduced compulsory WFH for all private and public sector employees, except for cases where on-site work is indispensable due to the nature of the work. This led to a six-fold increase in the share of remote workers within a couple of months. This stringent policy constitutes a massive exogenous shock in the worker-level adoption of WFH, well suited for studying.

Survey Design

To study the link between personality traits, teleworking, and productivity, we designed an original survey, implemented in May and June 2021 in Latvia. The target population was the set of employees who experienced work from home (only or mostly) during the pandemic. To reach this population, we used various channels: national news portals, social media (Facebook and Twitter) and radio advertisement. More than 2000 respondents participated in the survey, from which we obtained more than 1700 fully completed questionnaires.

Productivity and Remote Work

In addition to the standard individual characteristics such as age and the likes, we first collect information about respondents’ perception of their own relative productivity at the office and at home. More specifically, we ask “Where are you more productive?”. The five possible answers are “In office”, “In office (slightly)”, “No difference”, “At home (slightly)” and “At home” (plus a sixth answer: “Difficult to tell”). Table 1 provides a description of the answers. Roughly one third of the respondents reports a higher productivity at home, another third a higher productivity at the office, and one third do not report much of a difference. This measure of productivity is self-assessed, as it is the case with virtually any “Covid-19-era” paper on productivity. Note however that our question is not about absolute productivity as such, but relative productivity of teleworking in comparison with productivity at the office, which is arguably easier to self-assess.

Second, we ask “Talking about the job you worked at mostly remotely, and taking into account all difficulties and advantages, what would you choose post-pandemic: working from home or in office for the same remuneration (if you had the choice)?” The five possible answers are “Only from home”, “Mostly from home”, “Indifferent”, “Mostly in office”, “Only in office” (and a sixth option: “Difficult to tell”). The main aim of this question is to study who would like to keep working remotely in the post-pandemic period, irrespective of productivity concerns. Notably, the answers are much different than from the productivity question (see Table 1), which suggests the latter does not reflect preferences.

Finally, we ask respondents about the post-pandemic monthly wage premium required by the respondent to accept i) working at the office for individuals preferring to work from home; ii) working from home for individuals preferring to work at the office. Median values of these premia for workers with different preferences are reported in Table 1 (panel C). These values appear to be economically meaningful both in absolute terms and relative to the median net monthly wage in Latvia (which was 740 euro in 2021), reinforcing the reliability of the survey.

Table 1. Outcome variables


Source: reproduced from Gavoille and Hazans (2022).

Measuring Personality Traits

The survey contains a section aiming at evaluating the personality of the respondent through the lens of the so-called Five Factor Model of Personality. The psychometrics literature offers several standardized questionnaires allowing to build a measure for each of these five factors – Openness to Experience, Agreeableness, Extraversion, Emotional Stability and Conscientiousness. We rely on the Ten-Item-Personality-Inventory (TIPI) measure (Gosling et al., 2003). This test is composed by only ten questions, making it convenient for surveys, and it has been widely used, including in economics. As simple as this approach seems, the performance of this test has been shown to be only slightly below those with more sophisticated questionnaires, and to provide measures highly correlated with the existing alternative measures of personality traits.

Results

Overall, the results indicate that personality traits do matter for productivity at home vs. at the office. The personality trait most strongly related to all three outcome variables is Conscientiousness. Controlling for a battery of other factors, individuals with a higher level of conscientiousness are reporting a higher productivity when working from home as well as a higher willingness to keep working from home after the pandemic. This link is not only statistically significant but also economically meaningful: an individual with a level of conscientiousness in the 75th percentile is 8.4 percentage points more likely to report a higher productivity from home than a similar individual in the 25th percentile. Considering that the sample average is 31 percent, this difference is substantial.

Previous studies documented a positive correlation between Conscientiousness and key labor market outcomes such as wage, employment status and supervisor evaluation. A usual concern of employers is a possible negative selection of workers in teleworking. Observing that highly conscientious workers are more willing to work from home, where they are more productive, suggests that firms do not need to exert a very strict control on employees choosing to telework.

Openness to Experience shows a similar positive relationship with productivity. Extraversion on the other hand is only weakly negatively related to productivity. The relationship between this trait and willingness to work from home is however much stronger. These findings are intuitive: workers with a high Openness to Experience are more likely to cope easily with the important changes associated with switching to WFH. On the other hand, extravert individuals may find it more difficult to remain physically isolated from colleagues.

The literature studying the relationship between WFH and productivity suggests a conditional effect based on gender. In parallel, the literature investigating the role of personality traits on labor market outcomes also documents gender-specific patterns. As our work builds on these two strands of literature, we provide a heterogeneity analysis of the personality traits/productivity relationship conditional on gender.

When disaggregating the analysis by gender, it appears that the relationship between personality traits and productivity is stronger for women than for men. Conscientiousness and (to a smaller extent) Openness to Experience have a strong positive relationship with relative productivity of teleworking for women, while Extraversion and Agreeableness feature economically meaningful negative relationships. Noteworthy, the effects of Agreeableness and Openness to Experience do not concern the probability to be more productive at the office but only the willingness to work from home after the pandemic. For men, only Conscientiousness is significant, with a much smaller magnitude than for women.

Conclusion

We document that personality traits matter for changes in productivity when switching to a WFH regime. In particular, individuals with high levels of Conscientiousness are much more likely to report a better productivity from home than from the office. Additionally, Openness to Experience and Extraversion also do play a role.

Taken together, these results suggest that a one-size-fits-all policy is unlikely to maximize neither firms’ productivity nor workers’ satisfaction. It also highlights that when estimating firm-level ability in switching to remote work, characteristics of individual workers should be considered. In particular, employers practicing remote work should invest in socialization measures to compensate the negative effect of teleworking on the wellbeing of more extravert workers. Finally, several surveys (e.g., Barrero et al., 2021) document that more than a third of workers in the US would start looking for a new job allowing (some) work from home if their current employer would impose a strict in-office policy. Our results support this finding but also indicate that the opposite also holds: some workers would strongly oppose to remaining in a WFH setup after the pandemic. Personality traits are important determinants of the value attached to working from home.

Acknowledgement

This research is funded by Iceland, Liechtenstein and Norway through the EEA Grants. Project Title: The Economic Integration of the Nordic-Baltic Region through Labour, Innovation, Investments and Trade (LIFT). Project contract with the Research Council of Lithuania (LMTLT) No is S-BMT-21-7 (LT08-2-LMT-K-01-070).

References

Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

Detecting Labor Tax Evasion Using Administrative Data and Machine-Learning Techniques

20220516 Detecting Labor Tax Evasion Image 01

Labor tax evasion is a major policy issue that is especially salient in transition and post-transition countries. In this brief, we use firm-level administrative data, tax authorities’ audit data and machine learning techniques to detect firms likely to be involved in labor tax evasion in Latvia. First, we show that this approach could complement tax authorities’ regular practices, increasing audit success rate by up to 35%. Second, we estimate that about 30% of firms operating in Latvia between 2013 and 2020 are likely to underreport the wage of (some of) their employees, with a slightly negative trend.

Introduction

Tax evasion is a major policy issue that is especially salient in transition and post-transition countries. In particular, “envelop wage”, i.e., an unofficial part of the wage paid in cash, is a widespread phenomenon in Eastern Europe (European Commission, 2020). Putnins and Sauka (2021) estimate that the share of unreported wages in Latvia amounts to more than 20%. Fighting labor tax evasion is a key objective of tax authorities, which face two main challenges. The first is to make the best use of their resources. Audits are costly, so the choice of firms to audit is crucial. The second challenge is to track the evolution of the prevalence of labor tax evasion. For this purpose, most of the existing literature relies on survey data.

In our forthcoming paper (Gavoille and Zasova, 2022), we propose a novel methodology aiming at detecting tax-evading firms, using administrative firm-level data, tax authorities’ audit data and machine learning techniques.

This study provides two main contributions. First, this approach can help tax authorities to decide which firms to audit. Our results indicate that the audit success rate could increase by up to 20 percentage points, resulting in a 35% increase. Second, our methodology allows us to estimate the share of firms likely to be involved in labor tax evasion. To our knowledge, this paper is the first to provide such estimates, which are however of primary importance in guiding anti-tax evasion policy. We estimate that over the 2013-2020 period, about 30% of firms operating in Latvia are underreporting (at least some of) their workers’ wages.

Methodology

The general idea of our approach is to train an algorithm to classify firms as either compliant or tax-evading based on observed firm characteristics. Tax evasion, like any financial manipulation, results in artifacts in the balance sheet. These artifacts may be invisible to the human eye, but machine learning algorithms can detect these systematic patterns. Such methods have been applied to corporate fraud detection (see for instance Cecchini et al. 2010, Ravisankar et al. 2011, West and Bhattacharya 2016).

The machine learning approach requires a subsample of firms for which we know the “true” firm behavior (i.e., tax-evading or compliant) in order to train the algorithm. For this purpose, we propose to use a dataset on tax audits provided by the Latvian State Revenue Service (SRS), which contains information about all personal income tax (PIT) and social security contributions (SSC) audits carried out by SRS during the period 2013-2020, including the outcome of the audit. The dataset also contains a set of firm characteristics and financial indicators, covering both audited and non-audited firms operating in Latvia (e.g., turnover, assets, profit). Assuming that auditors are highly likely to detect misconduct (e.g., wage underreporting) if present, audit outcomes provide information about a firm’s tax compliance. Firms sanctioned with a penalty for, say, personal income tax fraud are involved in tax evasion, whereas audited-but-not-sanctioned firms can be assumed compliant. The algorithm learns how to disentangle the two types of firms based on the information contained in their balance sheets. Practically, we randomly split the sample of audited firms into two parts, the training and the testing subsamples. In short, we use the former to train the algorithm, and then evaluate its performance on the latter, i.e., on data that has not been used during the training stage. If showing satisfying performance on the training sample, we can then apply it to the whole universe of firms and obtain an estimate of the share of tax-evading firms.

In this study, we successively implement four algorithms that differ in the way they learn from the data: (1) Random Forest, (2) Gradient Boosting, (3) Neural Networks, and (4) Logit (for a review of machine learning methods, see Athey and Imbens, 2019). These four data mining techniques have previously been used in the literature on corporate fraud detection (see Ravisankar et al. 2011 for a survey). Each of these four algorithms has specific strengths and weaknesses, motivating the implementation and comparison of several approaches.

Results

Predictive Performance

Table 1 provides the out-of-sample performance of the four different algorithms. In other words, it shows how precise the algorithm is at classifying firms based on data that has not been included during the training stage. Accuracy is the percentage of firms correctly classified (i.e., the model prediction is consistent with the observed audit’s outcome). In our sample, about 44% of audited firms are required to pay extra personal income tax and social security contributions. This implies that a naive approach predicting all firms to be evading would be 44% accurate. Similarly, a classification predicting all firms to be tax compliant would be correct in 56% of the cases. This latter number can be used as a benchmark to evaluate the performance of the algorithms. ROC-AUC (standing for Area Under the Curve – Receiver Operating Characteristics) is another widespread classification performance measure. It provides a measure of separability, i.e., how well is the model able to distinguish between the two types. This measure is bounded between 0 and 1, the closer to 1 the better the performance. A score above 0.8 can be considered largely satisfying.

Table 1. Performance measures

Source: authors’ calculations

Random Forest is the algorithm providing the best out-of-sample performance, with more than 75% of the observations in the testing set correctly classified. Random Forest is also the best performing model according to the ROC-AUC measure, with performance slightly better than Gradient Boosting.

Our results imply that a naive benchmark prediction is outperformed by almost 20 percentage points by Random Forest and Gradient Boosting in terms of accuracy. It is important to emphasize that this improvement in performance is achieved using a relatively limited set of firm-level observable characteristics that we obtained from SRS (which is limited compared to what SRS has access to), and that mainly come from firms’ balance sheets. This highlights the potential gain of using data-driven approaches for the selection of firms to audit in addition to the regular practices used by the fiscal authorities. It also suggests a promising path for further improvements, as in addition to this set of readily available information the SRS is likely to possess more detailed limited-access firm-level data.

Share of Tax-Evading Firms Over Time and Across NACE Sectors

We can now apply these algorithms to the whole universe of firms (i.e., to classify non-audited firms). Figure 1 shows the share of firms classified as tax-evading over the years 2014 to 2019 for our two preferred algorithms – Gradient Boosting and Random Forest. Random Forest (the best performing algorithm) predicts that 30-35% of firms are involved in tax evasion, Gradient Boosting predicts a slightly higher share (around 40%). Both algorithms, especially Random Forest, suggest a slight reduction in the share of tax-evading firms since 2014.

Figure 1. Share of tax-evading firms over time

Source: authors’ calculations

The identified reduction, however, does not necessarily imply that the overall share of unreported wages has declined. In fact, existing survey-based evidence (Putnins and Sauka, 2021) indicate that the size of the shadow economy as a share of GDP remained roughly constant over the 2013-2019 period, and that there was no reduction in the contribution of the “envelope wages”. With our method, we are estimating the share of firms likely to be involved in labor tax evasion. Unlike the survey approach, our methodology does not allow the measurement of tax-evasion intensity. In other words, the share of non-tax compliant firms may have decreased, but the size of the envelope may have increased in firms involved in this scheme.

Next, we disaggregate the share of tax-evading firms by the NACE sector. Figure 2 displays the results obtained with Random Forest, our best performing algorithm.

Figure 2. Share of tax-evading firms by NACE, based on Random Forest

Source: authors’ calculations

First, the sector where tax evasion is the most prevalent is the accommodation/food industry, where the predicted share of tax-evading firms is 70-80%. Second, our results indicate that the overall decrease in the share of firms likely to evade is not uniform. It is mostly driven by the accommodation/food and manufacturing sectors. Other sectors remain nearly flat. This highlights the fact that labor tax evasion varies both in levels and in changes across sectors.

Conclusion

We show that machine learning techniques can be successfully applied to administrative firm-level data to detect firms that are likely to be involved in (labor) tax evasion. Machine learning techniques can be used to improve the selection of firms to audit in order to maximize the probability to detect tax-evading firms, in addition to the regular practices already used by SRS. Our preferred algorithms – Random Forest and Gradient Boosting – outperform the naive benchmark classification by almost 20 percentage points, which is a substantial improvement. Once implemented, the use of these tools can improve the audit effectiveness at virtually no extra cost.

Our findings also suggest a promising path for further improvements in the application of such methods. The improvement in predictive power achieved by our proposed algorithm is attained by using a limited set of variables readily available from the firms’ balance sheets. Given that SRS is likely to have access to more detailed firm-level information that cannot be provided to third parties, there is clear room for improving the performance of the algorithms by using such limited-access data.

Acknowledgement: The authors gratefully acknowledge funding from the Latvian State Research Programme “Reducing the Shadow Economy to Ensure Sustainable Development of the Latvian State”, Project “Researching the Shadow Economy in Latvia (RE:SHADE)”; project No VPP-FM-2020/1-0005.

References

Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

Foreign-Owned Firms and Labor Tax Evasion in Latvia

20211128 Foreign-Owned Firms Image 01

It is well-documented that foreign-owned firms often pay higher wages than domestic firms. This phenomenon is usually explained by foreign firms being more productive. In this brief, we discuss another mechanism that drives the wage premium for employees of foreign-owned firms. By comparing income and expenditures of households led by employees of foreign-owned firms, domestic firms and public enterprises in Latvia, we show that employees of foreign-owned firms receive less undeclared cash payments than employees of domestic firms.

Introduction

A vast economic literature documents a wage premium for employees of foreign-owned firms (e.g., Heyman et al., 2007; Hijzen et al., 2013). This can result from self-selection of foreign firms in highly productive sectors (Guadalupe et al., 2012) or from a productivity increase (Harding and Javorcik, 2012). In a recent paper (Gavoille and Zasova, 2021), we provide evidence of a third driver: foreign-owned firms are more (labor) tax compliant than domestic firms.

Envelope wage, i.e., an unreported cash-in-hand complement to the official wage, is a widespread phenomenon in transition and post-transition countries (e.g., Gorodnichenko et al., 2009 in Russia, Putninš and Sauka, 2015 in the Baltic States, Tonin, 2011 in Hungary). Employees are officially registered, but the income reported to tax authorities is only a fraction of the true income, the difference being paid in cash. If domestic firms are more likely to underreport wages than foreign-owned ones, the documented wage premium for employees of foreign-owned firms is overestimated.

Methodology and data

To compare the prevalence of income underreporting in foreign and domestic firms, we use an approach similar to Pissarides and Weber (1989). This approach is based on two main assumptions. First, even though households participating in an expenditure survey can have incentives to misreport their expenditures, they accurately report their expenditure on food.

The second assumption is that if all households would fully report their income, similar households would report a similar share of spending on food. If, however, a group of households is likely to underreport income, their fraction of income spent on food will systematically be higher than that of tax-compliant households. Using the propensity to food consumption of a group of households that cannot evade payroll tax as a benchmark, we can identify groups of tax-evading households by comparing their food consumption with the reference group.

In this brief, we mainly focus on three household groups: households where the head is an (1) employee of a foreign-owned firm (reference group), (2) employee of a public sector enterprise, and (3) employee of a domestic firm. We introduce public sector employees as an additional comparison group, since they cannot collude with employers to underreport wages. Hence, our approach allows us to test whether households in the third group are more likely to receive undeclared payment than households in the first group, and additionally test if our reference group is systematically different from public sector employees.

We estimate Engel curve-type relationships for food consumption for different types of households, i.e., we estimate how households’ food consumption varies with income depending on employment of the main breadwinner (employed in a foreign-owned firm, public sector enterprise, domestic firm or self-employed), controlling for various household characteristics (number of adults, size of household, place of residence, level of education of the main breadwinner, and other).

Our data comes from three sources. First, we use the 2020 round of the Latvian Household Budget Survey (HBS), which provides information on household consumption, income and characteristics in 2019. Second, we use an administrative matched employer-employee dataset providing information on reported wages for the whole population of employees in Latvia. We match the second database with HBS using (anonymized) individual IDs contained in both datasets. Finally, we use (anonymized) firm IDs contained in the second database to merge it with a third data source, which provides detailed information on firms’ foreign-ownership status.

Results

For simplicity, in the rest of the brief we denote “household where the head is an employee of a foreign-owned firm” as simply “foreign-owned households”. A similar simplification applies to other household groups.

Comparing domestic and foreign-owned households, domestic households spend a higher share of their income on food. Figure 1 plots a non-parametric Engel curve for the two groups. The two curves exhibit fairly similar behavior, but the Engel curve for domestic households always lies above the one for foreign-owned households: for a given income, domestic households always spend a larger fraction on food than foreign-owned ones.

Our model estimations provide two main results. First, we find that the net wage premium for employees of foreign firms is 13-35%, depending on the sample and the source of data on income. Second, we show that domestic households are more likely to underreport income than foreign-owned households. On average, domestic firm households are estimated to conceal 26% more income than foreign-owned ones. At the same time, public sector households do not exhibit a significantly different food consumption pattern than foreign-owned firm households. Assuming that public sector households cannot evade, foreign-owned firm households hence do not underreport. The estimated share of concealed income is even larger (about 40%) if we restrict our sample to households where the head is aged below 50 years and is full-time employed.

Figure 1. Engel curve

Source: authors’ calculations. Note: We follow Hurst et al. (2014). We regress (administrative) wage and food consumption separately on demographic controls to condition out these factors. We recenter the residuals at the unconditional averages for each group and use these residuals to estimate the Engel curve with a cubic spline.

Conclusions

In a context of widespread labor tax evasion, the observed wage premium for employees of foreign-owned firms can be driven by payroll tax compliance. How much of the wage premium can underreporting explain? Our results for Latvia suggest a net wage premium of 13% to 35% for the group of foreign-owned households. This roughly corresponds to the magnitude of the underreporting factor, indicating that nearly all of the wage premium can be explained by labor tax evasion. Even though the precise underreporting point estimates should be cautiously interpreted, and this 1-to-1 relation is anecdotal, this nevertheless highlights the potential importance of envelope wages in explaining the wage premium of employees of foreign-owned firms when labor tax evasion is prevalent.

Acknowledgement: This brief is based on a recent article published in Economics Letters (Gavoille and Zasova, 2021). The authors gratefully acknowledge funding from LZP FLPP research grant No.LZP-2018/2-0067 InTEL (Institutions and Tax Enforcement in Latvia).

References

Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

Foreign Investors on the Investment Climate in Latvia

Railway bridge across river Daugava representing Foreign Investors on the Investment Climate in Latvia FREE Network Image 01

This brief summarizes the results of an annual study on the development of the investment climate in Latvia from the viewpoint of key foreign investors – companies that have made the decision to invest in the country and have been operating here for a considerable time period. The study was initiated in 2015 and aims to assess investors’ evaluation of the government policy initiatives to improve the investment climate in Latvia. It also aims to provide an in-depth exploration of the main challenges for and concerns of the foreign investors, both by identifying problems and offering solutions. The study draws on a survey/ mini case studies of the key foreign investors in Latvia. Our findings suggest that in recent years, some progress has been achieved on a number of dimensions that are crucial for the competitiveness of the investment climate in Latvia, such as the political efforts by the government of Latvia to improve the investment climate, the overall attitude to foreign investors, and labour efficiency. At the same time, foreign investors see little, if any, improvement with regards to other key areas, such as the availability of labour, the quality of education, the court system, corruption and the shadow economy.

Introduction

The study on the development of the investment climate in Latvia from the viewpoint of key foreign investors in Latvia was first launched in 2015 by the Foreign Investors’ Council in Latvia (FICIL) in cooperation with the Stockholm School of Economics in Riga (SSE Riga). This study aims to foster evidence-based policy decisions and promote a favourable investment climate in Latvia by:

  • (i) Assessing how foreign investors evaluate the government’s efforts and current policy initiatives aimed towards improving the investment climate in Latvia, and
  • (ii) Providing an in-depth exploration of the main challenges and concerns for the foreign investors, both by identifying problems and offering solutions.

The study draws on a survey/mini case studies of the key foreign investors in Latvia. The first 2015 wave of the survey covered 28 key foreign investors in Latvia. Our panel has gradually expanded over time, reaching 47 participating companies in 2019. From September to early November 2019, we interviewed 47 senior executives representing companies that are key investors in Latvia. Altogether, these companies (including their subsidiaries) contribute to 23% of Latvia’s total tax revenue from foreign investors, 9% of the total profit and employ 11% of the total workforce employed by foreign investors in Latvia, where by foreign investors we mean companies with above a 145 000 EUR turnover and 50% foreign capital (data form Lursoft, 2018).

All interviews were conducted by FICIL board members. The guidelines for the interviews consist of the following key parts:

  • (i) Assessment of whether, according to foreign investors, the investment attractiveness of Latvia has improved during the past 12 months;
  • (ii) Assessment of the work of Latvian policy-makers in improving the investment climate during 2019;
  • (iii) Evaluation of progress in the major areas of concern identified by foreign investors in Latvia in 2015, including demography, access to labour, level of education and science, quality of business legislation, quality of the tax system, support from the government and communication with policy-makers, unethical or illegal behaviour on the part of entrepreneurs, unfair competition, uncertainty, the court system and the healthcare system in Latvia.

Furthermore, in the 2019 study we included questions related to some of the key issues discussed between foreign investors and policymakers during 2019, including the tax system, the stability of the financial sector and the quality of higher education and science in Latvia.

Investment Attractiveness of Latvia: Key Concerns of Foreign Investors in Latvia

The results of the 2019 study suggest that, even though the assessment of foreign investors with regards to the investment attractiveness of Latvia and the work of policy-makers to improve the investment climate in Latvia is still at the average level, it shows some positive tendencies. Namely, on a scale from 1 to 5, where ‘1’ means that there are no improvements at all, ‘3’ some positive improvements and ‘5’ significant improvements, the development of the investment climate in 2019 was evaluated as ‘2.6’ (‘2.5’ in 2018 and 2017). Furthermore, when asked to score the policy-makers’ efforts to improve the investment climate in Latvia, using a scale of 1-5, where ‘1’ and ‘2’ were fail and ‘5’ was excellent, investors responded with an average of ‘2.9’ in both the 2017 and 2018 studies, whereas in 2019, the score improved to ‘3.1’.

Foreign investors were also asked to evaluate whether there has been any progress within the key areas of concern as identified in 2015. The results of the most recent study suggest that the demographic situation, which in the long term reflects both the availability of labour and market size, is still among the key challenges for the foreign investors. Namely, on the scale from 1-5 (where an indicator value of 1 means that Latvia is not competitive and 5 means that Latvia is very competitive in this dimension), investors assessed the demographic situation of Latvia with only ‘1.5’ in 2019. Furthermore, as many as 35 (out of 47) foreign investors stated that they had not seen any progress in this area over the past 12 months. This lack of progress is, perhaps, not very surprising as demographic changes may take substantial time.

Another two key areas where investors would like to see more progress are the quality of education and science and the availability of labour. On a 5-point scale, the quality of education and science was evaluated with ‘2.7’ in 2019 (‘3.0’ in 2018, ‘3.1’ in 2017) and 30 out of the 47 investors interviewed have seen no progress in the development of education and science in Latvia over the past 12 months. The availability of labour was evaluated with ‘2.8’ in 2019 (‘2.7’ in 2018 and 2017); investors scored the availability of blue-collar labour with ‘2.4’ in 2019 (‘2.3’ in 2018, ‘2.5’ in 2017) and the availability of labour at management level with ‘3.1’ (‘3.0’ in 2018, ‘2.9’ in 2017). The majority, i.e. 39 of 47 investors have also seen no progress with regards to the access to labour during the past 12 months. In this context, however, it should be emphasised that the efficiency of labour is increasing in Latvia, according to foreign investors: in 2018, it was assessed with ‘2.9’, yet, in 2019, investors evaluated the efficiency of labour in Latvia with ‘3.4’ out of ‘5’.

The quality of health and social security as well as the quality of business legislation are yet another two indicators of the competitiveness of the investment climate in Latvia that have been evaluated around the average level of ‘3’. Further, 33 of 47 investors have seen no progress with regards to improvement of the healthcare system in Latvia over the past 12 months.

While the overall standard of living is evaluated rather positively at ‘3.8’ in 2019, there is still not much improvement in this indicator as compared to the previous three years. One encouraging result of the 2019 study is that according to foreign investors, the attitude towards foreign investors is gradually improving in Latvia: from ‘3.2’ and ‘3.1’ in 2016 and 2017 to ‘3.6’ in 2018 and reaching ‘3.7’ in 2019.

The foreign investors in Latvia who took part in the 2019 study also expressed an expert opinion with regards to whether there has been any progress during the previous 12 months in the other areas of concern. In this light, the perception of uncertainty should be highlighted. As many as 25 (out of 47 investors) have seen no progress in this area, 16 have seen partial progress and 6 stated that there has been progress in reducing uncertainty. The court system of Latvia is another area where many foreign investors have seen no progress, i.e. 22 said ‘no progress’, 23: ‘partial progress’ and only 1 that there has been progress in the development of the court system in Latvia.

Specific Issues: Tax System, Stability of the Financial System and Quality of Higher Education and Science

In the 2019 study, we also initiated an in-depth exploration related to three key issues of concern extensively discussed between foreign investors and Latvia’s government during the FICIL High Council 2019 spring meeting, and throughout the year 2019 in general. These are: (i) the tax system, (ii) the stability of the financial system, and (iii) the quality of higher education and science. Foreign investors were asked to comment on the current situation and progress over the past years, as well as to provide suggestions to the policymakers in order to improve the situation in the particular area.

(i) Tax system:

The most recent tax reform was implemented in 2018, and the newly elected government has announced that the next reform will take place in 2021. Therefore, this year we asked investors to evaluate the results of the previous tax reform in Latvia. We also asked investors to comment on whether the recent tax reform has brought any benefits to their company and the overall economy of Latvia. On average, foreign investors scored the results of the previous tax reform in Latvia with ‘3.1’, i.e. slightly above the average.

Overall, at least one part of the foreign investors who took part in the 2019 studies highlighted that the previous tax reform was a step ‘in the right direction’. In particular, the zero-rate on reinvested profit was highlighted by a large number of investors as a very positive improvement. In some cases, investors also praised the progressivity of labour tax rates. However, a number of foreign investors highlighted that the tax system has actually become more complex after the reform. Investors also expressed suggestions for further steps to improve the tax system in Latvia, and these are as follows:

Avoid uncertainty. Stability and predictability of the tax system is what the majority of the foreign investors wish to see. In essence, this means fewer changes to the tax system.

Simplify and explain. Investors highlight that paying taxes should be a “simple task” and easy to understand. According to the viewpoints of foreign investors, there is also the potential for improvement with regards to how the responsible organisations, such as the State Revenue Service, communicate changes in the tax system to the private sector.

(Continue) the shift from taxing labour to consumption. Some of the investors that took part in the 2019 studies see that the process has been initiated by the previous tax reform and recommend continuing in this direction.

(ii) Stability of the financial sector in Latvia.

On average, foreign investors evaluated the progress with regards to the effectiveness of combating economic and financial crime with 3.2, i.e. above average. We then asked foreign investors whether they have felt any negative effects on their companies with regards to the situations in the financial sector over the past 2 years. We received some positive opinions, yet the negative ones prevailed. Namely, foreign investors highlighted the reputation risks of Latvia that often impact upon the operation of their companies and create challenges when working with foreign banks.

(iii) Quality of university education and science in Latvia.

Here, foreign investors were asked to reflect upon whether they were aware of any activities that policymakers carried out during the past year to improve the situation. On a positive note, a number of investors mentioned the recent development of the University of Latvia and Riga Technical University’s campuses. Some investors also highlighted that the reform to change the governance model of higher education institutions, initiated by the Ministry of Education and Science, was a good step towards improving the quality of higher education and science in Latvia. However, we also received a number of negative opinions, such as “Nothing has been accomplished, just talking”.

When asked “What changes would you suggest to improve the quality of education and science in Latvia and why? How would this help the business environment, e.g. companies such as yours?”, foreign investors emphasised the following:

Higher education (and science) is too local, fragmented and outdated. In essence, investors pointed out that there are simply too many higher education institutions in Latvia, that they work with outdated methods and are afraid (with no good reason) to open up internationally – also by attracting top quality foreign staff.

Change the governance of higher education institutions in Latvia is another strong request from foreign investors in Latvia. Many investors believe that changes in the financing model should also follow.

Improved connection between education and science and the world of business was yet another important aspect which was highlighted during the 2019 interviews, and also strongly emphasised in the previous studies.

Further Investment Plans and Message to the Prime Minister

When asked whether they plan to increase their investments in Latvia, as many as 64% of the investors interviewed answered with ‘yes’ (in the 2018 study, 55% interviewed answered with ‘yes’), 25% said ‘no’ (35% in the 2018 study) and 11% answered that ‘it depends on the circumstances’ (10% in the 2018 study) or that they have not yet decided.

Finally, we invited foreign investors to send a message to the Prime Minister of Latvia: one paragraph on what should be done to improve the business climate in Latvia, from the viewpoint of a foreign investor. These messages closely parallel the other findings of the 2019 study, stressing a number of key concerns that foreign investors are still facing in Latvia: the situation with regards to demography, quality of education and science, availability of labour, challenges with corruption and the shadow economy as well as needs for improvements in the health care sector amongst others.

Conclusions

The findings of the 2019 study on the view of the key foreign investors of the investment climate in Latvia suggest that in recent years, some progress has been achieved on a number of dimensions, such as political effort to improve the investment climate, attitude towards foreign investors, and labour efficiency. At the same time, foreign investors see little, if any, improvement with regards to other key areas, such as the availability of labour, the quality of education, the court system, corruption and the shadow economy.

Our findings highlight the need to continue policy-makers’ efforts to improve the investment climate in Latvia and provide policymakers with better grounds for making informed policy decisions with respect to the entrepreneurship climate in Latvia. We also hope that our study will further facilitate constructive communication between foreign investors and the government of Latvia.

References

Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

Latvia Stumbling Towards Progressive Income Taxation: Episode II

20171015 Latvia Stumbling Towards Progressive Income Taxation Image 01

In August 2017, the Latvian parliament adopted a major tax reform package that will come into force in January 2018. This reform was a long-awaited step from the Latvian authorities to make the personal income tax more progressive. Some of the elements of the adopted reform, e.g. the changes in the basic tax allowance are estimated to help reducing the tax wedge on low wages and help addressing the problem of high income inequality. At the same time, the way the newly introduced progressive tax rate is designed will effectively lead to a reduction in the tax burden on labor and will hardly introduce any progressivity to the system.

In recent years, reducing income inequality has become one of the top priorities of the Latvian government. Income inequality in Latvia is higher than in most other EU and OECD countries, and the need to address this issue has been repeatedly emphasized by the Latvian officials, the European Commission, the World Bank and OECD.

The main reason for high income-inequality is a low degree of income redistribution ensured by the tax-benefit system. The personal income tax (PIT) has been flat since the mid-nineties. While the non-taxable income allowance introduces some progressivity to the system, the Latvian tax system is characterized by a very high tax burden on low wages, compared to other EU and OECD countries.

Since the beginning of 2017, the government has worked on an extensive tax reform package that was passed in the parliament in August and will become effective as of January 2018.

Two years ago, we wrote about the tax reform of 2016. In this brief, we estimate the effect of the 2018 reform on the tax burden on labour and income inequality. We will only consider changes in direct taxes on personal income – the changes in enterprise income tax and excise tax are outside the scope of our analysis. Parts of our estimations are done using the tax-benefit microsimulation model EUROMOD (for more details about the EUROMOD modelling approach, see Sutherland and Figari, 2013) and EU-SILC 2015 data.

Tax reform 2018

We focus our analysis on four elements of the reform that are expected to affect income inequality and that are described below. In our simulations, however, we take into account all changes in the PIT rules.

First, the flat PIT rate of 23% will be replaced by a progressive rate with three brackets: 20% (applied to annual income not exceeding 20,000 EUR), 23% (for annual income above 20,000 EUR and below 55,000 EUR) and 31.4% (applied to income exceeding 55,000 EUR per year).

Second, the maximum possible PIT allowance will be increased and the structure of the PIT allowance will be made more progressive. Latvia has a differentiated allowance since 2016, which means that individuals with lower incomes are eligible for a higher tax allowance. Figure 1 shows the changes in the non-taxable allowance that will be introduced by the reform. Another important change is that the differentiated allowance will be applied to the taxable income in the course of the year. The current system foresees that, during a calendar year, all wages are taxed applying the lowest possible allowance (60 EUR per month in 2017), but workers eligible for a higher allowance have to claim the overpaid tax in the beginning of the next year.

Figure 1. Basic PIT allowance before (2017) and after (2018-2020) the reform, EUR

Source: compiled by the authors.

Third, the rate of social insurance contributions will be increased by 1 percentage point. Social insurance contributions are capped and the cap will be increased from 48,600 EUR per year to 55,000 EUR per year, i.e. to the same income threshold that divides the top PIT bracket.

Finally, the reform will modify the solidarity tax – a tax, which was introduced in Latvia in 2016 and which is paid by top income earners. When this tax was initially introduced, one of its objectives was to eliminate the regressivity from the tax system caused by the cap on social insurance contributions. Hence, the rate of the solidarity tax was set at the same level as the rate of social insurance contributions and was effectively replacing social insurance contributions above the cap. The reform foresees that part of the revenues from the solidarity tax (10.5 percentage points) will be used to finance the top PIT rate. This element of the reform implies that after January 2018 those falling into the top PIT bracket will, in fact, not face a higher PIT rate than those falling into the second income bracket – the introduction of the top rate will be offset by the restructuring of the solidarity tax.

Results

There are four main findings. First, the reform will reduce the tax wedge on labor income, whereas the tax wedge on low wages will remain high by international standards. Second, most of the PIT taxable income earners (93.5%) will fall into the bottom income bracket. Hence the reform will effectively reduce the tax burden, while the effect on progressivity is very limited. Third, the (small) increase in tax progressivity is ensured mainly by changes in the tax allowance, while the effect of changes in the tax rate on progressivity is negligible: Even those few PIT payers that fall into the top tax bracket will not experience any increase in the tax burden due to a compensating change in the solidarity tax. Finally, it is mainly the households in the middle of the income distribution that will gain from the reform.

Effect on tax wedge

We start with a simple comparison of the average labor tax wedge in Latvia and other OECD countries for different wage levels before and after the reform. The tax wedge measures the share of total labor costs that is taxed away in the form of taxes or social contributions payable on employees’ income.

Table 1. Average tax wedge for single wage earners without dependents in Latvia and other OECD countries, before and after the reform

 

67% of average worker’s wage

 

100% of average worker’s wage

 

167% of average worker’s wage

OECD average in 2016, % (a) 32.3 36.0 40.4
Latvia 2016, % (a) 41.8 42.6 43.3
Latvia’s rank in 2016* (a) 6 11 16
Latvia 2018, % (b) 39.4 42.3 42.6
Latvia 2019, % (b) 39.1 42.1 42.6
Latvia 2020, %(b) 39.0 41.9 42.8

Source: (a) OECD and (b) authors’ calculations. Note: * Ranking across 35 OECD countries. Higher ranking implies higher tax wedge relative to other countries.

Table 1 shows that the tax wedge on low wages (67% of an average worker’s wage) in Latvia is pretty high. In 2016, it was the 6th highest across OECD countries, while the tax wedge on high incomes (167% of the wage) is much closer to the OECD average.

While the reform will slightly reduce the tax wedge for low wage earners (from 41.8% to 39.0% in 2020), it will still remain high by OECD standards. Despite an increase in PIT rate for high-income earners, the reform will also lower the tax wedge for those who earn 167% of the average wage. Why? The explanation comes from the income thresholds for the tax brackets. The income of those earning 167% of the average wage is estimated to fully fall into the first tax bracket in 2018–2019 and only slightly exceed the income bracket for the second PIT rate by 2020. This means that most of the incomes of people earning 167% of the average wage will be taxed at the rate of 20%, which is lower than the current flat rate of 23%. Moreover, in 2020, only a small share of their income will be taxed at 23% – the same rate that these individuals would have had faced in the absence of the reform. Hence, we observe a reduction in the tax wedge for high-income earners.

Generally, only a very small share of taxpayers will fall into the middle and the top income brackets. According to our estimations, as many as 93.5% of all PIT taxable income earners will fall into the lowest income bracket, and only about 6.5% will fall into the second income bracket and about 0.5% will face the top PIT rate.

Apart from the progressive PIT schedule, the reform envisages important changes in the solidarity tax. As explained above, part of the revenues from the solidarity tax will be used to finance the top PIT rate. Therefore, even those (very few) taxpayers whose income will exceed the threshold for the top PIT rate, will not experience any increase in the tax burden because of the compensating change in the solidarity tax. Therefore, the reform will effectively reduce the tax burden on labour with very little effect on progressivity.

While lowering the tax burden is generally welcome, the motivation for applying the top rate to such a small group of taxpayers is not clear. For example, in their recent in-depth analysis of the Latvian tax system, the World Bank (World Bank, 2016) came up with a tax reform proposal that envisaged a considerably lower threshold for the top PIT rate, which, according to our estimations, would cover about 12% of the taxpayers. Given the limited budget resources and an especially high tax wedge on low wages, a more targeted reduction in the tax burden would be preferable. Similar concerns about insufficient reduction in the tax burden on low-income earners are expressed in the latest OECD economic survey of Latvia (OECD, 2017).

Effect on income distribution

Below we present the results from the tax-benefit microsimulation model EUROMOD. Figure 2 shows the simulated change in equivalized disposable income by income deciles compared to the baseline “no-reform” scenario in 2018-2020.

Figure 2. Change in equivalized disposable income by income deciles caused by the reform compared to “no-reform” scenario, %

Source: authors’ calculations using EUROMOD-LV model

The first thing to note is that these are mainly households in the middle of the income distribution who will gain from the reform – their income will increase due to both the increase in non-taxable allowance and the introduction of the progressive rate.

The gain in the bottom of the income distribution is smaller for several reasons. First, the proportion of non-employed individuals (unemployed and non-active) is larger in the bottom deciles. Second, individuals with low wages are less likely to gain from the reduction in the tax rate and the increase in the basic allowance, since they might already have most of their income untaxed due to the currently effective basic allowance. The same applies to pensioners who have a higher basic allowance than the employed individuals and who are mainly concentrated in the bottom of income distribution.

Our results suggest that the wealthiest households will also see their incomes grow as a result of the reform (by about 1% in 10th decile). The growth is ensured by the fact that annual income below 20,000 EUR will be taxed at a reduced rate of 20%, and, taking into account that even in the top decile only about half of the individuals get income from employment that exceeds 20,000 EUR per year, the gain from the tax reduction is considerable even in the top decile. A reduction in the tax allowance for high-income earners will have a negative effect on wealthy individuals’ income, but this will be more than compensated by the above positive effect of the change in the tax rate. Hence, the net effect on the incomes in the top deciles is estimated to be positive.

Finally, Table 2 summarizes the effect of the reform on the income distribution, measured by the Gini coefficient on equivalized disposable income. On the whole, the reform is estimated to slightly reduce income inequality – in 2020, the Gini coefficient is expected to be 0.6 points lower than it would have been in the absence of the reform. This reduction is mainly driven by the changes in the non-taxable allowance, while the three PIT rates are estimated to have an increasing impact on income inequality.

Table 2. Gini coefficient on equivalized disposable income in the reform and “no-reform” scenario

2018 2019 2020
“No-reform” scenario 35.2 35.4 35.7
Reform scenario 35.0 35.0 35.1

Source: authors’ calculations using EUROMOD-LV model

Conclusion

The 2018 tax reform was a long-awaited step from the Latvian authorities on the way to a more progressive tax system. The planned changes in the basic tax allowance are estimated to help reducing the tax wedge on low wages and help addressing the problem of high income-inequality.

At the same time, the second major aspect of the reform, the introduction of a progressive PIT rate, raises more questions than answers. The progressive rate, the way it is designed, will effectively lead to an across-the-board reduction of the tax burden on labor and will hardly help to reach the proclaimed objective of taxing incomes progressively. Given the limited budgetary resources and given that taxes on low wages will remain high compared to other countries even after the reform, a more targeted reduction of the taxes on low-income earners would have been a more preferred option.

References

  • OECD, 2017. “OECD Economic Surveys: Latvia 2017”, OECD Publishing, Paris. http://dx.doi.org/10.1787/eco_surveys-lva-2017-en
  • Sutherland, H. and Figari, F., 2013. “EUROMOD: the European Union tax-benefit microsimulation model”, International Journal of Microsimulation, 1(6), 4-26.
  • World Bank, 2016. “Latvia Tax Review”, available at http://fm.gov.lv/files/nodoklupolitika/Latvia%20Tax%20Review%20Draft%20231216%20D.pdf

Save

Save

Higher Competition in the Domestic Market – A Way to Boost Aggregate Productivity

20170227 Higher Competition in the Domestic Market - FREE Policy Brief

Competition is a good thing not only because of lower prices and larger variety. Higher competition in the domestic market also shifts necessary labour and capital resources from less productive domestic-oriented firms to export-oriented productivity champions. Such firms will make better use of production factors and generate larger output. Thus, simply increasing the level of competition in the domestic market can boost the aggregate productivity of a country.

The aggregate productivity of a country can be boosted even without changing the productivity of individual enterprises. This can be achieved by improving the allocation of resources – the redistribution of labour and capital towards more productive firms. These firms will make better use of production factors and generate larger output. But how can one affect the allocation of resources? Economic theory says that allocation depends on the productivity of individual firms: more productive enterprises attract more labour and capital. However, there exists another factor behind allocation: distortions.

Distortions affect the allocation of resources

A model developed by Hsieh and Klenow (2009) – one of the most popular frameworks to study the allocation of resources – has a very important and realistic feature: it acknowledges that firms are not treated equally. Some firms may face lower supply of banking loans ending with higher capital costs. Other firms could confront with trade unions and higher wages. Tax rates may also differ across firms. These are all examples of distortions. Firms facing larger distortions are forced to underuse respective production factor, while firms that enjoy more favourable conditions tend to overuse capital and labour, generating more output.

While it is virtually impossible to imagine an economy without any distortions (the one where all firms face the same taxes, costs of labour, capital etc.), not all distortions damage the allocation of resources. Only distortions to productive firms create misallocation of resources by shifting labour and capital towards unproductive firms. Thus, removal of such distortions can improve the efficiency of allocation and raise the aggregate output of the country.

According to Hsieh and Klenow (2009) the distortions faced by every individual firm can be quantified from the balance sheets and profit/loss data. For example, observing lower-than-usual ratio of capital to intermediate inputs (comparing with other enterprises in a narrowly defined industry) indicates a capital distortion, possibly related with limited access to banking loans. Similarly, lower-than-usual share of wages in total production costs implies high labour distortions. Finally, the size of the distortion can be detected as a case of abnormally low share of intermediate inputs in total output, and signals about the restrictions to total output (e.g. due to higher taxes for large enterprises).

Misallocation of resources is small in Latvia

In my recent research (see Benkovskis, 2015), I use anonymised firm-level dataset for 2007–2013 and apply the Hsieh and Klenow (2009) model to study the allocation of resources in Latvia – a unique example of a small and open economy facing extreme structural shifts during the financial crisis. According to my estimates, the negative contribution of misallocation to aggregate productivity was close to 27% in 2013 (see Figure 1). In other words, it suggests that actual aggregate productivity could be boosted by 27% if all distortions were removed!

This may seem large but in fact 27% is a comparatively low figure. Hsieh and Klenow (2009) argue that full liberalisation would boost aggregate manufacturing productivity by 86–115% in China, 100–128% in India, and 30–43% in the US. Dias et al. (2015) show that removing distortions would lead to a 30% gain in output of Portugal in 2011. Thus, misallocation of resources is relatively small in Latvia. Even more important: the misallocation of resources decreased after the crisis in Latvia (contrary to the case of Portugal), adding more than 10 percentage points to aggregate productivity growth between 2010 and 2013.

Figure 1. Contribution from misallocation of resources to aggregate total factor productivity, %

Source: Benkovskis (2015). Note: shows the contribution of misallocation comparing with the counterfactual case of no distortions.

The finding that allocation of resources improved after the crisis is interesting per se, but uncovering the reasons behind the improvement is even more important. Figure 1 provides a decomposition, which shows that labour distortions are minor in Latvia due to high flexibility of labour market (in line with recent findings by Braukša and Fadejeva, 2016). The capital distortions, while being minor in 2007–2008, increased afterwards, pointing to some credit supply constraints faced by the highly productive enterprises after the financial crisis. However, by far largest contribution comes from the misallocation of intermediate inputs – the turnover of the most productive firms face some constraints. And it was the ease of constraints to turnover for the most productive firms that determined the improvements in aggregate productivity since 2010.

The level of competition matters for misallocation

My research stresses the importance of the competition level on the market, since higher competition serves as a natural constraint for the firm to increase its turnover. What if the most productive Latvia’s firms systematically come up against higher competition? I found that indeed this is the case. First, recent results by Fadejeva and Krasnopjorovs (2015) show that Latvia’s domestic market has lower competition level comparing with external markets. Second, it is widely acknowledged that exporters tend to be more productive comparing with domestically oriented firms (see e.g. Bertou et al., 2015, who report positive export premiums for EU countries, while Benkovskis and Tkačevs, 2015, find higher productivity of exporters in Latvia). Thus, Latvia’s productive export-oriented firms are subject to higher competition and cannot enlarge their turnover as easy as other entities. This shifts labour and capital towards small and less productive firms working solely on domestic market, creating the misallocation of resources.

The domestic competition factor can also explain the improving allocation of resources after 2010. The study by Fadejeva and Krasnopojorovs (2015) reveals that the competition gap between domestic and foreign markets narrowed after the financial crisis (see Table 1). Namely, life was too easy on the local Latvia’s market during the boom time, allowing unproductive firms to survive and drain away resources from more productive firms. But conditions became tougher after the crisis (although the competition level still remained lower than abroad). We can view this as a “cleansing effect of the crisis”: some of the least productive domestic oriented firms went bankrupt (or decreased their turnover), freeing the necessary capital and labour resources for productive exporters.

Table 1: Change in the competitive pressure on main product in domestic and foreign markets compared to the situation before 2008, %

Domestic market Foreign market
2008–2009 2010–2013 2008–2009 2010–2013
Strong decrease 2.9 2.2 0.9 1.0
Moderate decrease 11.8 3.8 7.6 5.9
Unchanged 33.8 24.7 45.7 51.5
Moderate increase 30.0 28.1 25.2 19.7
Strong increase 18.7 38.5 11.2 8.8
Does not apply 2.8 2.8 9.4 13.1

Source: Fadejeva and Krasnopjorovs (2015), Table A.102. Notes: based on the sample of 557 Latvia’s firms; results are weighted to represent firm population.

Conclusion

This research has an important policy conclusions applicable to any country that seeks to increase aggregate productivity. The competition level in the domestic market is important not only for consumers, who enjoy lower prices and higher variety. Higher competition in the domestic market also shifts necessary resources from less productive domestic-oriented firms to export-oriented productivity champions.

References

Save

Save