Location: Latvia
Minimum Wage Spike and Income Underreporting
The labor markets of many transition countries are characterized by two features: a spike at the minimum wage level in the wage distribution and widespread use of so-called envelope wages, i.e. non-declared cash payments in addition to the official wage. In this brief, we present a body of suggestive evidence showing that tax evaders are overrepresented among minimum wage earners in Latvia.
Introduction
Labor markets in many transition and post-transition countries are characterized by the prevalence of payroll tax evasion in the form of envelope wages, i.e. non-declared cash in addition to the official wage (see for instance Putnins and Sauka (2015) for Latvia, Paulus (2015) and Kukk and Staehr (2014) for Estonia and Bíró et al. (2022) and Elek et al. (2012) for Hungary).
Another defining characteristic of these transition economies is a very large peak at exactly the minimum wage in the wage distribution. To explain this phenomenon, Tonin (2011) argues that the mass of individuals at the minimum wage level is composed to a large extent of workers receiving envelope wages, where employers and employees collude and agree on reporting only the minimum wage to minimize tax liabilities while remaining under the radar of the tax authorities. In such a setup, the minimum wage policy becomes an enforcement tool for the fiscal administration, as it pushes non-compliant firms to convert part of the envelope wage into an official wage so that it reaches the new minimum wage.
However, only scarce concrete evidence shows that payroll tax evaders are overrepresented among minimum wage earners. Considering the regular minimum wage hikes in the region (e.g., a 95 percent increase in Latvia in 2010-2022 and a planned increase by another 24 percent in 2023), understanding the interaction between minimum wage policy and labor tax evasion is crucial.
In this brief, we present a body of suggestive evidence highlighting the prevalence of wage underreporting at exactly the minimum wage level in Latvia.
Data and Methodology
We use Latvian administrative employer-employee data for 2011 to 2015, covering the full Latvian employed population at a monthly rate. To identify tax evasion, we rely on the comparison between small and large firms. The literature studying tax evasion provides considerable evidence showing that small firms tend to evade more taxes than large firms. Kleven et al. (2016) provide a theoretical foundation for this result, showing that collusive evasion is more difficult to sustain in firms with more employees. Empirically, this effect has been documented in many countries (see for instance Putnins and Sauka (2015), Gavoille and Zasova (2021), and Benkovskis and Fadejeva (2022) for the results on Latvia, Bíró et al. (2022) for Hungary, Paulus (2015) for Estonia, and Kumler et al. (2020) for Mexico).
In this brief, we use a very broad definition for firm size categories and divide firms into firms employing 30 or fewer employees as small and firms with more than 30 employees as large. With such a crude definition, it is inevitable that firms below and above the threshold are highly heterogeneous, implying that some firms below the threshold are tax-compliant, while some firms above the threshold are tax-evading. For our purposes though, it is sufficient to assume that the share of evading employees in small firms is larger than that in the sample of large firms.
Results
We begin by plotting the distribution of wages in the private sector. Figure 1 plots monthly wages in the range of 0–1000 Euros in 2011. The right most dashed vertical line in the figure marks the minimum wage (284.57 Euros per month in 2011) and the left most dashed line marks 50 percent of the minimum wage. There are clear spikes at the minimum wage (and at half of the minimum wage). The minimum level wage spike in small firms (top graph) is much more pronounced than in large firms (bottom graph), which is consistent with the idea that the spike is driven by income underreporting.
Figure 1. Gross wage distribution in the private sector in small (< 30 empl.) and large (> 30 empl.) firms in 2011.

Note: Micro enterprises are excluded. Vertical lines depict the minimum wage (284.57 Euro) and half of the minimum wage (142.29 Euro) in 2011. Source: Authors’ calculations.
This explanation implies that employers and employees choose to declare employment and underdeclare earnings instead of staying completely informal, which is consistent with the available evidence. Staying completely informal involves much higher risks of detection if authorities perform regular inspections of workplaces, and in many Central European countries with prevalent income underreporting, completely informal employment is not very common (OECD, 2008). In Latvia, firms have to register employees in the electronic system of the State Revenue Service before they start to work, hence the probability that an unofficially employed person is detected during a workplace inspection is very high (State Labor Inspectorate, 2010). Existing empirical evidence on Latvia also suggests that income underreporting is much more widespread than completely informal employment, which is estimated at only 2–3.5 percent (European Commission, 2014; Hazans, 2012). Hence, we interpret the spikes as indicative of tax evaders bunching at the minimum wage.
Wage Growth Among Minimum Wage Earners
Wages are expected to grow with tenure, but if minimum wage earners receive part of their income in cash, their reported wage can remain unchanged even after years of employment within a firm (as any increase would arguably go through the non-declared cash). To examine if this is the case, we exploit a period when there were no changes in the Latvian minimum wage (January 2011–December 2013). We select employees who were employed by the same firm in all months of 2011–2013, assign them to wage bins according to their wage in 2011, and in each wage bin calculate the share of workers whose wage in 2013 was the same as in 2011. We assign workers to 10-Euro bins, with the exception of minimum wage earners, whom we assign to a bin of 1 Euro.
As evident from Figure 2 minimum wage earners clearly stand out from other employees. In small firms, almost 45 percent of employees earning the minimum wage in 2011 had the same reported wage in 2013. There is also a spike at the minimum wage in large firms (28 percent), but it is less pronounced than in small firms.
Figure 2. Proportion of continuously employed workers facing no wage growth between 2011 and 2013, by wage bins, in small (< 30 empl.) and large (> 30 empl.) firms.

Note: Micro enterprises and public sector firms are excluded. Source: Authors’ calculations.
An alternative explanation for the large share of minimum wage earners who experience no wage growth could be that, for many of them, the minimum wage is binding. To rule this out, we perform the same calculations on a sample of young employees (24 or younger in 2011). Workers in the early stages of their careers tend to have higher returns to experience and tenure; thus, young workers are less likely to have no wage growth after three years of employment with the same firm. Figure 3 plots the results for young workers. In large firms, the spike at the minimum wage is more than twice as small as for the full sample of workers (12 percent vs. 28 percent), but in small firms it remains very high (33 percent).
Figure 3. Proportion of continuously employed young workers (aged 24 or less in 2011) facing no wage growth between 2011 and 2013, by wage bins, in small (< 30 empl.) and large (> 30 empl.) firms.

Note: Micro enterprises and public sector firms are excluded. Source: Authors’ calculations.
Conclusion
This brief documents highly prevalent tax evasion among minimum wage earners in Latvia. In such a context, the minimum wage is a powerful fiscal instrument as a higher minimum wage pushes non-compliant firms to disclose a larger share of their employees’ true earnings. In addition, wage underreporting among minimum wage earners can act as a shock absorber and cushion the negative employment effects of a minimum wage hike in countries where a large share of workers officially receive the minimum wage.
These upsides however come at a cost. The results presented in this brief by no means imply that all minimum wage earners are tax evaders; a notable share of employees receiving the minimum wage on paper do honestly earn only the minimum wage. In our paper (Gavoille and Zasova, 2022), we show that the flip side of the positive fiscal effect of a minimum wage hike is job losses among genuine low-wage earners and closures of tax-compliant firms that are affected by the hikes.
Acknowledgement
This brief is based on a recent article published in the Journal of Comparative Economics (Gavoille and Zasova, 2022). The authors gratefully acknowledge funding from LZP FLPP research grant No.LZP-2018/2-0067 InTEL (Institutions and Tax Enforcement in Latvia).
References
- Benkovskis, Konstantins; and Ludmila Fedejeva, 2022. “Chasing the Shadow: the Evaluation of Unreported Wage Payments in Latvia“. Latvijas Banka, Working Paper Nr. 1/2022.
- Bíró , Anikó; Dániel Prinz, and László Sándor, 2022. “The minimum wage, informal pay, and tax enforcement“. Journal of Public Economics, 215, 104728.
- Elek, Péter; János Köllő, Balázs Reizer, and Péter A. Szabó, 2012. “Chapter 4 Detecting Wage Under-Reporting Using a Double-Hurdle Model“. Emerald Group Publishing Limited, Rochester, NY, pp. 135–166.
- European Commission, 2014. “Undeclared Work in the European Union“, Special EUROBAROMETER 284.
- Gavoille, Nicolas; and Anna Zasova, 2022. “Minimum wage spike and income underreporting: A back-of-the-envelope-wage analysis“, Journal of Comparative Economics, forthcoming.
- Gavoille, Nicolas; and Anna Zasova, 2021. “What we pay in the shadow: Labor tax evasion, minimum wage hike and employment“. SSE Riga/BICEPS Research paper No.6.
- Hazans, Mihails, 2012. “How many people are working without a contract in Latvia and neighboring countries?”. Technical Report, University of Latvia.
- Kumler, Todd; Eric Verhoogen, and Judith Frías, 2020. “Enlisting Employees in Improving Payroll Tax Compliance: Evidence from Mexico“. The Review of Economics and Statistics, 102 (5), 881–896.
- Kukk, Merike; and Karsten Staehr, 2014. “Income underreporting by households with business income: evidence from Estonia“. Post-Communist Economies, 26(2), 257-276.
- OECD, 2008. “Declaring Work or Staying Underground“. OECD employment outlook 2008.
- Paulus, Alari, 2015. “Tax Evasion and Measurement Error: an Econometric Analysis of Survey Data Linked with Tax Records“. Working Paper 2015-10. ISER Working Paper Series.
- Putnins, Talis; and Arnis Sauka, 2015. “Measuring the shadow economy using company managers“, Journal of Comparative Economics, 43(2), 471-490.
- State Labor Inspectorate, 2010. “Latvia: Annual Report 2010”
- Tonin, Mirco, 2011. “Minimum wage and tax evasion: Theory and evidence“. Journal of Public Economics, 95(11-12), 1635-1651.
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
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
- Barrero, J. M., Bloom, N. and Steven, D. (2021). Why working from home will stick, NBER Working Paper 28731.
- Bartik, A., Cullen, Z., Glaeser, E., Luca, M. and Stanton, C. (2020). What jobs are being done at home during the COVID-19 crisis? Evidence from firm-level surveys, NBER Working Paper 27422.
- Bick, A. and Blandin, A. (2021). Real-time labor market estimates during the 2020 coronavirus outbreak.
- Dingel, J. and Neiman, B. (2021). How many jobs can be done at home?, Journal of Public Economics, 189, 104235.
- Gavoille, N. and Hazans, M. (2022). Personality traits, remote work and productivity, IZA Discussion Paper 15486.
- Gosling, S., Rentfrow, P. and Swann, W. (2003). A very brief measure of the Big-Five personality domains. Journal of Research in personality, 37(6), pp. 504-528.
- Heckman, J., Stixrud, J. and Urzua, S. (2006). The effects of cognitive and noncognitive abilities on labor market outcomes and social behavior, Journal of Labor economics, 24(3), pp. 411-482.
- Heckman, J. and Tim Kautz. (2012). Hard evidence on soft skills. Labour Economics, 19(4), pp. 451-464.
- Sostero, M., Milasi, S., Hurley, J., Fernandez-Macias, H. and Bisello, M. (2020). Teleworkability and the COVID-19 crisis: a new digital divide?, JRC Working Papers Series on Labour, Education and Technology, No. 2020/05.
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
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
- Athey, Susan, and Guido Imbens. 2019. “Machine Learning Methods That Economists Should Know About.” Annual Review of Economics 11: 685–725.
- Cecchini, Mark, and Haldun Aytug, and Gary J. Koehler, and Praveen Pathak, 2010. “Detecting management fraud in public companies“. Management Science 56, 1146-1160.
- European Commission, 2020. “Undeclared Work in the European Union. Special Eurobarometer 498” (Report)
- Gavoille, Nicolas and Anna Zasova, 2022. “Estimating labor tax evasion using tax audits and machine learning”, SSE Riga/BICEPS Research papers, forthcoming.
- Putnins, Talis, and Arnis Sauka, 2021. “Shadow Economy Index for the Baltic Countries 2009–2020” (Report), SSE Riga
- Ravisankar, Pediredla, and Vadlamani Ravi, and Gundumalla Raghava Rao, and Indranil Bose, 2011. “Detection of financial statement fraud and feature selection using data mining techniques“. Decision Support Systems, 50(2), 491-500.
- West, Jarrod, and Maumita Bhattacharya, 2016. “Intelligent financial fraud detection: a comprehensive review“. Computers & security, 57, 47-66
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.
Understanding the Economic and Social Context of Gender-based and Domestic Violence in Central and Eastern Europe – Preliminary Survey Evidence
This brief presents preliminary findings from a cross-country survey on perceptions and prevalence of domestic and gender-based violence conducted in September 2021 in eight countries: Armenia, Belarus, Georgia, Latvia, Poland, Russia, Sweden and Ukraine. We discuss the design and content of the study and present initial information on selected topics that were covered in the survey. The collected data has been used in three studies presented at the FROGEE Conference on “Economic and Social Context of Domestic Violence” and offers a unique resource to study gender-based violence in the region.
While the COVID-19 pandemic has amplified the academic and policy interest in the causes and consequences of domestic violence, the Russian invasion of Ukraine has tragically reminded us about the gender dimension of war. There is no doubt that a gender lens is a necessary perspective to understand and appreciate the full consequences of these two ongoing crises.
The tragic reason behind the increased attention given to domestic violence during the COVID-19 lockdowns is the substantial evidence that gender-based violence has intensified to such an extent that the United Nations raised the alarm about a “shadow pandemic” of violence against women and girls (UN Women on-line link). Already before the pandemic, one in three women worldwide had experienced physical or sexual violence, usually at the hands of an intimate partner, and this number has only been increasing. The tragic reports from the military invasion of Ukraine concerning violence against women and children, as well as information on the heightened risks faced by war refugees from Ukraine, most of whom are women, should only intensify our efforts to better understand the background behind these processes and study the potential policy solutions to limit them to a minimum in the current and future crises.
The most direct consequences of gender-based and domestic violence – to the physical and mental health of the victims – are clearly of the highest concern and are the leading arguments in favour of interventions aimed at limiting the scale of violence. One should remember though, that the consequences and the related social costs of gender-based and domestic violence are far broader, and need not be caused by direct acts of physical violence. Gender-based and domestic violence can take the form of psychological pressure, limits on individual freedoms, or access to financial resources within households. As research in recent decades demonstrates, such forms of abuse also have significant consequences for the psychological well-being, social status, and professional development of its victims. All these outcomes are associated with not only high individual costs, but also with substantial social and economic costs to our societies.
This policy brief presents an outline of a survey conducted in eight countries aimed at better understanding the socio-economic context of gender-based violence. The survey, developed by the FREE Network of independent research institutes, has a regional focus on Central and Eastern Europe, with Sweden being an interesting benchmark country. The data was collected in September 2021 in Armenia, Belarus, Georgia, Latvia, Poland, Russia, Sweden and Ukraine. The socio-economic situation of all these countries irrevocably changed with the Russian invasion of Ukraine on 24 February 2022, the ongoing war, and its dramatic consequences. The world’s attention focused on the unspeakable violence committed by the Russian forces in Ukraine, the persecution in Belarus and Russia of their own citizens who were protesting against the invasion, and the challenges other neighbouring countries have faced as a result of an unprecedented wave of Ukrainian refugees. This change, on the one hand, calls for a certain distance with which we should judge the survey data and the derived results. On the other hand, the data may serve as a unique resource to support the analysis of the pre-war conditions in these countries with the aim to understand the background driving forces behind this dramatic crisis. In as much as the gender lens is necessary to comprehend the full scale of the consequences of both the COVID-19 pandemic and the war in Ukraine, it will be equally indispensable in the process of post-war development and reconciliation once peace is again restored.
Survey Design, Countries, and Samples
The survey was conducted in eight countries in September 2021 through as a telephone (CATI) survey using the list assisted random digit dialling (LA-RDD) method covering both cell phones and land-lines, and the sampling was carried out in such a way as to make the final sample representative of the respective populations by gender and three age group (18-39; 40-54; 55+). The collected samples varied from 925 to 1000 individuals. The same questionnaire initially prepared as a generic English version was fielded in all eight countries (in the respective national languages). The only deviations from the generic version were related to the education categories and to a set of final questions implemented in Latvia, Russia and Ukraine with a focus on the evaluation of national IPV legislation.
Table 1 presents some basic sample statistics, while Figure 1 shows the unweighted age and gender compositions in each country. The proportion of women in the sample varies between 49.4% in Sweden and 55.0% in Belarus, Russia and Ukraine. The average sample age is between 43 (Armenia) and 51 (Sweden), while the proportion of individuals with higher education is between 29.3% in Belarus and 55.4% in Georgia. The highest proportion of respondents living in rural areas could be found in Armenia at 62.9%, while the lowest was in Georgia at 24.1%. Figure 1 illustrates good coverage across age groups for both men and women.
Table 1. FROGEE Survey: samples and basic demographics

Source: FROGEE Survey on Domestic and Gender-Based Violence.
Figure 1. FROGEE Survey: gender and age distributions

Source: FROGEE Survey on Domestic and Gender-Based Violence.
Socio-economic Conditions and Other Background Characteristics
To be able to examine the relationship between different aspects of domestic and gender-based violence to the socio-economic characteristics of the respondents, an extensive set of questions concerning the demographic composition of their household and their material conditions were asked at the beginning of the interview. These questions included information about partnership history and family structure, the size of the household and living conditions, education and labour market status (of the respondent and his/her partner) and general questions concerning material wellbeing. In Figure 2 we show a summary of two of the latter set of questions – the proportion of men and women who find it difficult or very difficult to make ends meet (Figure 2A) and the proportion who declared that the financial situation of their household deteriorated in the last two years, i.e. since September 2019, which can be used as an indicator of the material consequences of the COVID-19 pandemic. We can see that the difficulties in making ends meet are by far lowest in Sweden, and slightly lower in the other EU countries (Latvia and Poland). The differences are less pronounced with regard to the implication of the pandemic, but also in this case respondents in Sweden seem to have been least affected.
Figure 2. Making ends meet and the consequences of COVID-19
a. Difficulties in making ends meet

b. Material conditions deteriorated since 2019

Source: FROGEE Survey on Domestic and Gender-Based Violence.
Perceptions and Incidence of Domestic and Gender-Based Violence and Abuse
Frequency of differential treatment and abuse
The set of questions concerning domestic and gender-based violence started with an initial module related to the different treatment of men and women, with respondents asked to identify how often they witnessed certain behaviours aimed toward women. The questions covered aspects such as women being treated “with less courtesy than men”, being “called names or insulted for being a woman” and women being “the target of jokes of sexual nature” or receiving “unwanted sexual advances from a man she doesn’t know”, and the respondents were to evaluate if in the last year they have witnessed such behaviours on a scale from never, through rarely, sometimes, often, to very often. We present the proportion of respondents answering “often” or “very often” to two of these questions in Figure 3A (“People have acted as if they think women are not smart”) and 3B (“A woman has been the target of jokes of a sexual nature”). We find significant variation across these two dimensions of differential treatment, and we generally find that women are more sensitive to perceiving such treatment. It is interesting to note that the proportion of women who declared witnessing differential treatment in Sweden is very high in comparison to for example Latvia or Belarus, which, as we shall see below, does not correspond to the proportion of women (and men) witnessing more violent types of behaviour against women.
Figure 3. Frequency of differential treatment (often or very often)
a. People have acted as if they think women are not smart

b. A woman has been the target of jokes of a sexual nature

Source: FROGEE Survey on Domestic and Gender-Based Violence.
Questions on the frequency of witnessing physical abuse were also asked in relation to the scale of witnessed behaviour. Here respondents were once again asked to say how often “in their day-to-day life” they have witnessed specific behaviours. These included such types of abuse as: a woman being “threatened by a man”, “slapped, hit or punched by a man”, or “sexually abused or assaulted by a man”. The proportion of respondents who say that they have witnessed such behaviour with respect to two of the questions from this section are presented in Figure 4. In Figure 4A we show the proportion of men and women who have witnessed a woman being “slapped, hit or punched” (sometimes, often or very often), while in Figure 4B being “touched inappropriately without her consent”. Relative to the perceptions of differential treatment the incidence of a woman being hit or punched (4A) declared by the respondents seems more intuitive when considered against the overall international statistics of gender equality. The proportions are lowest in Sweden and Poland, and highest in Armenia and Ukraine. However, the perception of inappropriate touching by men with respect to women (Figure 4B) shows a similar extent of such actions across all analysed countries.
Figure 4. Frequency of abuse (sometimes, often or very often)
a. A woman has been slapped, hit or punched by a man

b. A woman has been touched inappropriately, without her consent, by a man

Source: FROGEE Survey on Domestic and Gender-Based Violence.
Perceptions of abuse
The questions concerning the scale of witnessed behaviours were complemented by a module related to the evaluation of certain behaviours from the perspective of their classification as abuse and the degree to which certain types of gender-specific behaviours are acceptable. Thus, for example respondents were asked if they consider “beating (one’s partner) causing severe physical harm” to be an example of abuse within a couple (Figure 5A) or if “prohibition to dress as one likes” represents abuse (Figure 5B). This module included an extensive list of behaviours, such as “forced abortion”, “constant humiliation, criticism”, “restriction of access to financial resources”, etc. As we can see in Figure 6, with respect to the clearest types of abuse – such as physical violence – respondents in all countries were pretty much unanimous in declaring such behaviour to represent abuse. With respect to other behaviours the variation in their evaluation across countries is much greater – for example, while nearly all men and women in Sweden consider prohibiting a partner to dress as he/she likes to be abusive (Figure 5B), only about 57% of women and 36% of men in Armenia share this view.
The questionnaire also included questions specifically focused on the perception of intimate partner violence. These asked respondents if they knew about women who in the last three months were “beaten, slapped or threatened physically by their intimate partner”, and the evaluation of how often intimate partners act physically violent towards their wives.
Figure 5. Perceptions of abuse: are these examples of abuse within a couple?
a. Beating causing severe physical harm

b. Prohibition to dress as one likes

Source: FROGEE Survey on Domestic and Gender-Based Violence.
A further evaluation of attitudes towards violent behaviour was done with respect to the relationship between a husband and wife and his right to hit or beat the wife in reaction to certain behaviours. In Figure 6 we show the distribution of responses regarding the justification for beating one’s wife in reaction to her neglect of the children (6A) or burning food (6B). The questions also covered such behaviour as arguing with her husband, going out without telling him, or refusing to have sex. As we can see in Figure 6, once again we find substantial country variation in the proportion of the samples – both men and women – who justify such violent behaviour within couples. This was particularly the case when respondents were asked about justification of violent behaviour in the case of a woman neglecting the children. In Armenia as many as 30% of men and 22% of women agree that physical beating is justified in those cases. These proportions are manyfold greater than what can be observed in countries such as Latvia, where 3% of men and women agreed that abuse was justifiable under these circumstances, or Sweden, where only 1% of men and women agreed.
Figure 6. Perceptions of abuse: is a husband justified in hitting or beating his wife
a. If she neglects the children

b. If she burns the food

Source: FROGEE Survey on Domestic and Gender-Based Violence.
Seeking help and the legal framework
The final part of the questionnaire focused on the evaluation of different reactions to incidents of domestic and gender-based violence. Respondents were first asked if a woman should seek help from various people and institutions if she is beaten by her partner – respondents were asked if she should seek help from the police, relatives or friends, a psychologist, a legal service or if, in such situations, she does not need help. In Figure 7 we show the proportion of people who agreed with the last statement, i.e. claimed that it is only the couple’s business. The proportions of respondents who declare such an attitude is higher among men than women within each country, and is highest among men in Armenia (48%) and Georgia (25%). Again, these proportions are in stark contrast to men in Sweden, or even Poland, where only 4% and 8% of men agreed, respectively. Nevertheless, looking at the total survey sample, a vast majority believe that a woman who is a victim of domestic violence should seek help outside of her home, indicating that at least some forms of institutionalised support for women are popular measures with most people.
Figure 7. Proportions agreeing that domestic violence is only the couple’s business

Source: FROGEE Survey on Domestic and Gender-Based Violence.
The interview also included questions on the need for specific legislation aimed at punishing intimate partner violence and on the existence of such legislation in the respondents’ countries. The latter questions were extended in three countries – Latvia, Russia and Ukraine – to evaluate the specific sets of regulations implemented recently in these countries and to facilitate an analysis of the role IPV legislation can play in reducing violence within households. Legislation on domestic violence is relatively recent. During the last four decades, though, changes accelerated in this respect around the world. Legislative measures have been introduced in many countries, covering different aspects of preventing, protecting against and prosecuting various forms of violence and abuse that might happen within the marriage or the family. Research strives to offer evaluations on what legal provisions are most effective, in a setting in which statistics and information are still far from perfect, and as a consequence of the dearth of strong evidence the public debate on the matter is often lively. For legislation to have an effect on behaviour through shaping the cost of committing a crime, on the one hand, and the benefit of reporting it or seeking help, on the other, or more indirectly through changing norms in society, information and awareness are key. For how can deterrence be achieved if people do not know what the sanctions are? And how can reporting be encouraged if victims do not know their rights? The evidence on legislation awareness is unfortunately quite scarce. A survey of the criminology field (Nagin, 2013) concludes that this is a major knowledge gap.
Figure 8 shows the proportions of answers to questions concerning the need for and existence of legislation specifically targeted towards intimate partner violence. We can see that while support for such legislation is quite high (Figure 8A), it is generally lower among men (in particular in Armenia, Russia and Belarus). Awareness of existence of such laws, on the other hand, is much lower, and it is particularly low among women. It should be pointed out that all countries have in fact implemented provisions against domestic violence in their criminal code, but only around half of the population, sometimes much fewer, are aware of that.
Figure 8. Need for and awareness of IPV legislation
a. State should have specific legislation aimed at punishing IPV

b. Country has specific legislation aimed at punishing intimate partner violence

Source: FROGEE Survey on Domestic and Gender-Based Violence.
Recent reforms of DV legislation that were implemented in Russia in 2017, in Ukraine in 2019 and in Latvia just a few months ago (at the time of the survey, the changes were at the stage of a proposal) were the subject of the final survey questions in these countries. We find that awareness of these recent reforms is very low in all three countries, and knowledge about the reform content (gauged with the help of a multiple-choice question with three alternative statements) is even lower. Our analysis suggests that gender and family situation are the two factors that most robustly predict support for legislation, while education and age are associated with awareness and knowledge of the reforms. Minority Russian speakers are less aware of the reforms in both Ukraine and Latvia, in Ukraine are also less likely to answer correctly about the content of the reform, and in Latvia are less supportive of DV legislation in general.
Analyses of this type are useful for policy design, to better understand which groups lack relevant knowledge and should be targeted by, for example, information campaigns to combat DV, such as those many governments around the world implemented during the covid-19 pandemic.
Future Work Based on the Survey
The above is just a small sample of the rich source of information that has resulted from conducting the survey. Already from this simple overview we can see some interesting results. There are, for example, clear differences between men and women in perceptions of how common certain types of abusive behaviour are. However, for many questions differences between countries are larger than those between men and women within a country. Interestingly such differences are also different depending on the severity of the abuse or violence. In Sweden the perception of women being victims of less violent abuse is higher than in some other countries where instead some more violent types of abuse are reported as being more common. This could, of course, be due to actual differences in actual events but it is also possible that there are differences in what types of behaviour are considered to represent harassment and abuse in different societies. More careful data work is needed to try to answer questions like this and many others. Currently there are a number of ongoing research projects based on the survey results, three of which will be presented at the FREE-network conference on “Economic and Social Context of Domestic Violence” in Stockholm on May 11, 2022. Our hope is that this work will help in taking actions to prevent gender-based abuse and domestic violence based on a better understanding of underlying cross-country differences in social norms and attitudes and their relation to socio-economic factors.
About FROGEE Policy Briefs
FROGEE Policy Briefs is a special series aimed at providing overviews and the popularization of economic research related to gender equality issues. Debates around policies related to gender equality are often highly politicized. We believe that using arguments derived from the most up to date research-based knowledge would help us build a more fruitful discussion of policy proposals and in the end achieve better outcomes.
The aim of the briefs is to improve the understanding of research-based arguments and their implications, by covering the key theories and the most important findings in areas of special interest to the current debate. The briefs start with short general overviews of a given theme, which are followed by a presentation of country-specific contexts, specific policy challenges, implemented reforms and a discussion of other policy options.
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
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
- Gavoille, Nicolas; and Anna Zasova, 2021. “Foreign ownership and labor tax evasion: Evidence from Latvia”, Economics Letters, 207, 110030.
- Gorodnichenko, Yuriy; and Jorge Martinez‐Vazquez; and Klara Sabirianova Peter, 2009. “Myth and Reality of Flat Tax Reform: Micro Estimates of Tax Evasion Response and Welfare Effects in Russia“, Journal of Political Economy, 117 (3), pages 504-554.
- Guadalupe, Maria; and Olga Kuzmina; and Catherine Thomas, 2012. “Innovation and Foreign Ownership“, American Economic Review, 102 (7), pages 3594-3627.
- Harding, Torfinn; and Beata S. Javorcik, 2012. “Foreign Direct Investment and Export Upgrading“, The Review of Economics and Statistics, 94 (4), pages 964–980.
- Heyman, Fredrik; and Fredrik Sjöholm; and Patrik Gustavsson Tingvall, 2007. “Is there really a foreign ownership wage premium? Evidence from matched employer–employee data“, Journal of International Economics, 73 (2), pages 355-376.
- Hijzen, Alexander; and Pedro S. Martins; and Thorsten Schank; and Richard Upward, 2013. “Foreign-owned firms around the world: A comparative analysis of wages and employment at the micro-level“, European Economic Review, 60, pages 170-188.
- Hurst, Erik; and Geng Li; and Benjamin Pugsley, 2014. “Are Household Surveys Like Tax Forms? Evidence from Income Underreporting of the Self-Employed“, The Review of Economics and Statistics, 96 (1), pages 19–33.
- Pissarides, Christopher A.; and Guglielmo Weber, 1989. “An expenditure-based estimate of Britain’s black economy“, Journal of Public Economics, Volume 39 (1), pages 17-32
- Putninš, Tālis J.; and Arnis Sauka, 2015. “Measuring the shadow economy using company managers“, Journal of Comparative Economics, 43 (2), pages 471–490.
- Tonin, Mirco, 2011. “Minimum wage and tax evasion: Theory and evidence“, Journal of Public Economics, 95 (11–12), pages 1635-1651.
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
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
- Lursoft (2018). Official company statistics of Latvia, 2018.
- FICIL Sentiment Index (2019), https://www.sseriga.edu/centres/csb/sentiment-index
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 Long Shadow of Transition: The State of Democracy in Eastern Europe
In many parts of Eastern Europe, the transition towards stronger political institutions and democratic deepening has been slow and uneven. Weak political checks and balances, corruption and authoritarianism have threatened democracy, economic and social development and adversely impacted peace and stability in Europe at large. This policy brief summarizes the insights from Development Day 2019, a full-day conference organized by SITE at the Stockholm School of Economics on November 12th. The presentations were centred around the current political and business climate in the Eastern European region, throwing light on new developments in the past few years, strides towards and away from democracy, and the challenges as well as possible policy solutions emanating from those.
The State of Democracy in the Region
From a regional perspective, Eastern Europe has seen mixed democratic success over the years with hybrid systems that combine some elements of democracy and autocracy. Based on the V-Dem liberal democracy index, ten transition countries that have joined the EU saw rapid early progress after transition. In comparison, the democratic development in twelve nations of the FSU still outside of the EU has been largely stagnant.
In recent years, however, democracy in some of those EU countries, such as Bulgaria, the Czech Republic, Hungary, Poland and Romania have been in decline. Poland, one of the region’s top performers in terms of GDP growth and life expectancy, has experienced a sharp decline in democracy since 2015. Backlashes have often occurred after elections in which corruption and economic mismanagement have led to the downfall of incumbent governments and a general distrust of the political system. Together with low voter turnout, this created fertile ground for more autocratic forces to gain power helped by demand for strong leadership.
An example from Ukraine illustrated the role of media, both traditional and social, for policy-making. In some countries of the region, traditional media is strictly state-controlled with obvious concerns for democracy. This is less the case in Ukraine, where also social media plays an important role in forming political opinions. The concern is that, as elsewhere, opinions that gain traction on social media may not be impartial or well informed, affecting public perception about policy-making. A recent case showing the popular reaction to an attack on the former governor of the Central Bank suggests that those implementing important reforms may not get due credit when biased and partial information dominates the political discourse on social media.
Another case is the South Caucasian region: Armenia, Georgia and Azerbaijan. The political situation there has been characterized as a “government by day, government by night” dichotomy, implying that the real political power largely lies outside the official political institutions. In Georgia, the situation can be described as a competition between autocracy and democracy, with a feudalistic system in which powerful groups replace one another across time. As a result, trust in political institutions is low, as well as citizens’ political participation.
In the case of Azerbaijan, there is an elected presidency, but in reality, power has been passed on hereditarily, becoming a de facto patrimonial system. Lastly, in Armenia, the new government possesses democratic credentials, but the tensions with neighbouring Azerbaijan and Turkey have given increasing power to the military and important economic powers. Overall, democratisation in these countries has been hindered by a trend for powerful politicians to form parties around themselves and to retain power after the end of their mandates. Also, the historical focus on nation-building in these countries has led to a marked exclusion of minorities and a conflict of national identities.
The last country case in this part of the conference focused on the current political situation in Russia and on the likely outcomes after 2024. The social framework in Russia appears constellated by fears – a fear of a world war, of regime tightening and mass repressions, and of lawlessness – all of them on the rise. Similarly, the economy is suffering, in particular from low business activity, somewhat offset by a boost in social payments. Nonetheless, it was argued that it is not economic concerns, but rather political frustration, that has recently led citizens to take to the street. Despite this, survey data shows that trust in Putin is still over 60%, and that most people would vote for him again. However, survey data also points out that the most likely determinant of this trust is the lack of another reference figure, and that citizens are not averse to the idea of political change in itself. Lastly, Putin will most likely retain some political power after 2024, transiting “from father to grandfather of the nation”.
Voices from the civil society in the region also emphasized the importance of a free media and an active civil society to prevent the backsliding of democracy. With examples from Georgia and Ukraine, it was argued that maintaining the independence of the judiciary, as well as the public prosecutor’s office, can go a long way in building credibility both among citizens and the international community. The European Union can leverage the high trust and hopeful attitudes it benefits from in the region to push crucial reforms more strongly. For example, more than 70% of Georgians would vote for joining the EU if a referendum was held on the topic and the European Union is widely regarded as Georgia’s most important foreign supporter.
Weak Institutions and Business Development
The quality of political and legal institutions strongly affects the business environment, in particular with regards to the protection of property rights, rule of law, regulation and corruption. Research from the European Bank for Reconstruction and Development (EBRD) highlights that the governance gap between Eastern Europe and Central Asia and most advanced economies is still large, even though progress in this area has actually been faster than for other emerging economies since the mid-‘90s. This is measured through enterprise surveys as well as individual surveys. In Albania, for instance, a perception of lower corruption was linked to a decrease in the intention to emigrate equivalent to earning 400$ more per month. Another point concerned the complexity of measuring the business environment and the benefits of firm-level surveys asking firms directly about their own actual experience of regular enforcement. For example, in countries such as Poland, Latvia and Romania the actual experience of business regulation measured via the EBRD’s Business Environment Enterprise Performance Survey, is far worse than one would expect from the World Bank’s well known Doing Business rating.
From the perspective of Swedish firms, trade between Sweden and the region has remained rather flat in the past years, as the complexity and risks of these markets especially discourage SMEs. Business Sweden explained that Swedish firms considering an expansion in these markets are concerned with issues of exchange rate stability, and the institutional-driven presence of unfair competition and of excessive bureaucracy. Moreover, inadequate infrastructure and the presence of bribery and corruption make everyday business operations risky and costly. It was generally emphasized that countries have to create a safe investment environment by reducing corruption, establishing a clear and well enacted regulatory environment, having dependable courts and strengthening domestic resource mobilization. Swedish aid can play a part, but there is a need to develop new ways of delivering aid to make it more effective.
An interesting example is Belarus, that has seen more economic and political stability than most neighbours, but at the same time a lack of both economic and political reforms towards market economy and democracy. Gradually the preference towards private ownership, as opposed to public, has increased in recent years and the country has seen a rising share of the private sector, even without specific privatization reforms. Nonetheless, international businesses are still reluctant to invest due to high taxes, a lack of access to finance as well as to a qualified workforce, but most importantly due to the weak legal system. An exception has been China, and Belarus has looked at the One Belt One Road Initiative as a promising bridge to the EU. Scandals connected with the two main Chinese-invested projects have damped the enthusiasm recently, though.
The economic and political risks of extensively relying on badly diversified energy sources, as is the case with natural gas imports from Russia in many transition states were also discussed. It was shown how some countries such as Ukraine, Poland and Lithuania have improved their energy security by either benefitting from reverse-flow technology and the EU’s bargaining power or building their own LNG terminals to diversify supply sources. However, either of these, as well as other energy security improving solutions are likely to come with an economic cost, though, that not all countries in the region can afford.
A Government Perspective
The main focus of this section was the Swedish government’s new inspiring foreign policy initiative, “Drive for Democracy”. Drawing from a definition of democracy by Kerstin Hesselgren, an early Swedish female parliamentarian, democracy enables countries to realize and utilize the forces of the individual and draw them into a life-giving, value-creating society. It was emphasized that the values of democracy are objectives by themselves (e.g. freedom of expression, respect for human rights) but also that democracy has important positive effects in other areas of human welfare. The Swedish government views democracy as the best foundation for a sustainable society, equality of opportunity and absence of gender or racial bias.
The “Drive for Democracy” specifically identifies Eastern Europe as one of the main frontiers between democracy and autocracy, and the Swedish government promotes human rights and stability through various bilateral programmes through the Swedish International Development Cooperation Agency, Sida, and multilateral initiatives within the EU, such as the Eastern Partnership. It was also emphasized that democracy is a continuous process that can always be improved, as indeed experienced by Sweden. Political rights were granted to women only in 1919 followed by convicts and prisoners in 1933 and to the Roma people only in 1950. Political and democratic rights are thus never once and for all given, and it is crucial that the dividends from democracy are carried forward to the younger generation.
Conclusion
In sum, the day illustrated clearly how democracy engages all segments of society, from the business sector to civil society, and the potential for but also challenges involved for democratic deepening in Eastern Europe. To get more information about the presentations during the day, please visit our website.
Participants at the Conference
- PER OLSSON FRIDH, State Secretary, Ministry for Foreign Affairs.
- ALEXANDER PLEKHANOV, Director for Transition Impact and Global Economics at EBRD.
- TORBJÖRN BECKER, Director, SITE.
- CHLOÉ LE COQ, Associate Professor, SITE and Professor of Economics, University of Paris II Panthéon-Assas.
- THOMAS DE WAAL, Senior Fellow at Carnegie Endowment for International Peace.
- NATALIIA SHAPOVAL, Vice President for Policy Research at Kyiv School of Economics.
- ILONA SOLOGUB, Scientific Editor at VoxUkraine and Director for Policy Research at Kyiv School of Economics.
- KETEVAN VASHAKIDZE, President at Europe Foundation, Georgia.
- MARIA BISTER, Senior Policy Specialist, Sida.
- HENRIK NORBERG, Deputy Director, Ministry for Foreign Affairs.
- YLVA BERG, CEO and President, Business Sweden.
- LARS ANELL, Ambassador and formerly Volvo’s Senior Vice President.
- ERIK BERGLÖF, Professor in Practice and Director of the Institute of Global Affairs, London School of Economics and Political Science.
- KATERYNA BORNUKOVA, Academic Director, BEROC, Minsk.
- ANDREI KOLESNIKOV, Senior Fellow, Carnegie Moscow Center.
Liberal Democracy in Transition – The First 30 Years
This year marks 30 years since the first post-communist election in Poland and the fall of the Berlin Wall. Key events that started a dramatic transition process from totalitarian regimes towards liberal democracy in many countries. This brief presents stylized facts from this process together with some thoughts on how to get this process back on a positive track. In general, the transition countries that joined the EU are still far ahead of the other transition countries in terms of democratic development.
The recent decline in democratic indicators in some EU countries should be taken seriously as they involve reducing freedom of expression and removing constraints on the executive, but should also be discussed in light of the significant progress transition countries entering the EU have shown during the first 30 years of transition. The brief shows that changes in a democracy can happen fast and most often happen around elections, so getting voters engaged in the democratic process is crucially important. This requires politicians that engage the electorate and have an interest in preserving democratic institutions. An important question in the region is what the EU can do to promote this, given its overloaded political agenda. Perhaps it is time for a Greta for democracy to wake up the young and shake up the old.
This brief provides an overview of political developments in transition countries since the first post-communist elections in Poland and the fall of the Berlin Wall 30 years ago. It focuses on establishing stylized facts based on quantitative indices of democracy for a large set of transition countries rather than providing in-depth studies of a small number of countries. The aim of the brief is thus to find common patterns across countries that can inform today’s policy discussion on democracy in the region and inspire future studies of the forces driving democracy in individual transition countries.
The first issue to address is what data to use to establish stylized facts of democratic development in the region. By now, there are several interesting indicators that describe various aspects of democratic development, which are produced by different organizations, academic institutions and private data providers. In this brief, three commonly used and well-respected data providers will be compared in the initial section before we zoom in on more specific factors that make up one of these indices.
The big picture
The three indicators that we look at first are: political rights produced by Freedom House; polity 2 produced by the Polity IV project; and the liberal democracy index produced by the V-Dem project. Figures 1-3 show the unweighted average of these indicators for two groups of countries. The EU10 are the transition countries that became EU members in 2004 and 2007 and include Bulgaria, the Czech Republic, Estonia, Hungary, Lithuania, Latvia, Poland, Romania, Slovakia, and Slovenia. The second group, FSU12, are the 12 countries that came out of the Soviet Union minus the three Baltic countries in the EU10 group, so the FSU12 group consists of Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, Kyrgyzstan, Moldova, Russia, Tajikistan, Turkmenistan, Ukraine, and Uzbekistan.
Figure 1. Freedom House

Source: Freedom House and author’s calculations
Note: Scale inverted, 1 is best and 7 worst score
Figure 2. Polity IV project

Source: Polity IV project and author’s calculations
Note: Scale from -10 (fully autocratic) to 10 (fully democratic)
Figure 3. V-Dem

Source: V-Dem project and author’s calculations
Note: Scale from 0 to 1 where higher is more democratic
All three indicators convey the message that the democratic transformation in the EU10 group was very rapid in the early years of transition and the indicators have remained at high levels since the mid-90s only to show some decline in the most recent years for two of the three indicators. The FSU12 set of countries have made much less progress in terms of democratic development and remain far behind the EU10 countries in this regard. Overall, there is little evidence at the aggregate level that the democratic gap between the EU10 and FSU12 groups is closing. While the average EU10 country is more or less a full-fledged democracy, the average FSU12 country is at the lower end of the spectrum for all three democracy measures.
The average indicators in Figures 1-3 obviously hide some interesting developments in individual countries and in the following analysis, we will take a closer look at the liberal democracy index at the country level. We will then investigate what sub-indices contribute to changes in the aggregate index in the countries that have experienced significant declines in their liberal democracy scores.
For the first part of the analysis, it is useful to break down the democratic development in two phases. The first phase is from the onset of transition (1989, 1991 or 1993 depending on the specific country) to the time of the global financial crisis in 2009 and the second phase is from 2009 to 2018 (the last data point).
Figure 4. Liberal democracy, the first phase

Source: V-Dem project and author’s calculations
Figures 4 and 5 compare how the liberal democracy indicator changes from the first year of the period (measured on the horizontal axis) to the last year of the period (on the vertical axis). The smaller blue dots are the individual countries that make up the EU10 group while the red dots are the FSU12 countries. The 45-degree line indicates when there is no change between start and end years, while observations that lie below (above) the line indicate a deterioration (improvement) of the liberal democracy index in a specific country.
In the first phase of transition (Figure 4), all of the EU10 countries increased their liberal democracy scores and the average increase for the group was almost 0.5, going from 0.26 to 0.74. This was a result of many of the countries in the group making significant improvements without any countries deteriorating. The FSU12 group had a very different development with the average not changing at all since the few countries that improved (Georgia and Ukraine) were counterbalanced by a significant decline in Belarus and a more modest decline in Armenia.
Figure 5. Liberal democracy, the second phase

Source: V-Dem project and author’s calculations
The very rapid improvement in the liberal democracy index in the EU10 countries in the first phase of transition came to a halt and also reversed in several countries in the second phase of transition. Of course, as they had improved so much in the first period, there was less room for further positive developments, but the rapid decline in some of the countries was still negative news. However, it does point towards that reform momentum was very strong in the EU accession process, but once a country had entered the union, the pressure for liberal democratic reforms has faded.
Overall, the EU10 average fell by 0.1 from 2009 to 2018. This was a result of declining scores in several countries. The particularly large declines in this period have been seen in Hungary (-0.28), Poland (-0.27), Bulgaria (-0.14), the Czech Republic (-0.14), and Romania (-0.12). Again, the average FSU12 score did not change much, although Ukraine (-0.2) put its early success in reverse and lost as much in this period as it had gained earlier.
Country developments
Since much of the current discussion centers on how democracy is being under attack, the figures name the countries that have seen significant declines in the liberal democracy score in the first or second phase of transition. Figures 6 and 7 show the time-series of the liberal democracy index in the countries with significant drops at some stage of the transition process.
Figure 6. FSU12 decliners

Source: V-Dem project and author’s calculations
In many countries, the drop comes suddenly and sharply, with the first and most prominent example being Belarus. There, it only took three years to go from one of the highest ranked FSU12 countries to fall to one of the lowest liberal democracy scores. In Poland, Romania, Bulgaria and Armenia, the process was also very rapid and significant changes happened in 2-3 years.
Figure 7. EU10 decliners

Source: V-Dem project and author’s calculations
In the Czech Republic and Hungary, the period of decline was much longer and in the case of Hungary, the drop was the most significant in the EU10 group. Ukraine stands out as more of an exception with a roller-coaster development in its liberal democracy score that first took it up the list and then back down to where it started. For those familiar with politics in these countries, it is easy to identify the elections and change in government that have occurred at the times the index has started to fall in all of these countries. In other words, the democratic declines have not started with coups but followed election outcomes where in most cases the incumbent leaders have been replaced by a new person or party.
How democracy came under attack
We will now take a closer look at what has been behind the instances of decline in the aggregate index by investigating how the sub-indices have developed in these countries. The sub-indices that build up the liberal democracy index are: freedom of expression and alternative sources of information; freedom of association; share of population with suffrage; clean elections; elected officials; equality before the law and individual liberty; judicial constraints on the executive; and legislative constraints on the executive (the structure is a bit more complex with mid-level indices, see V-Dem 2019a).
Table 1 shows how these indicators have changed in the time period the liberal democracy indicator has fallen significantly (with shorter versions of the longer names listed above but in the same order). The heat map of decline indicated by the different colours is constructed such that positive changes are marked with green, smaller declines are without colour, declines greater that 0.1 but smaller than 0.2 are in yellow and larger declines in red. Note that the liberal democracy index is not an average of the sub-indices but based on a more sophisticated aggregation technique (see V-Dem 2019b). Therefore, the Czech Republic and Bulgaria can have a greater fall in top-level liberal democracy index that what is indicated by the sub-indices.
Table 1. Changes in liberal democracy indicators at times of democratic decline

Source: V-Dem project and author’s calculations
For the countries with the largest changes in the liberal democracy index, it is clear that both freedom of expression and alternative sources of information have come under attack together with reduced judicial and legislative constraints on the executive. Among the EU10 countries, Hungary and Poland stand out in terms of reducing freedom of expression, while Romania has seen most of the decline coming from reducing constraints on the executive. Not surprisingly, Belarus stands out in terms of the overall decline in liberal democracy coming from reducing both freedom of expression and constraints on the executive in the most significant way.
On a more general level, the attack on democracy does differ between the countries, but in the cases where serious declines can be seen, the attack has been particularly focused on information aspects and constraints on the executive. At the same time, all countries let all people vote (suffrage always at 1) and let the one with the most votes get the job (elected officials).
Policy conclusions
This brief has provided some stylized facts on the first 30 years of liberal democracy in transition and some details on how democracy has come under attack in individual countries. It leaves open many questions that require further studies and some of these are indeed ongoing in this project and will be presented in future briefs and policy papers here.
Some observations have already been made here that can inform policy discussions on liberal democratic developments in the region. The first is that changes can happen very rapidly, both in terms of improvements but also in terms of dismantling important democratic institutions, including those that provide constraints on the executive or media that provides unbiased coverage before and after elections. What is also noteworthy is that these changes have almost always happened after an election where a new person or party has come to power, so the democratic system is used to introduce less democracy in this sense.
It is also interesting that in all of the countries, the most easily observed indicators of democracy such as suffrage and having the chief executive or legislature being appointed by elections are given the highest possible scores. In other words, even the most autocratic regime wants to look like a democracy; but as the old saying goes, “it is not who votes that is important, it is who counts”.
The regime changes at election times that have led to declining liberal democracy scores have also in many cases come as a result of the incumbents not doing a great job or voters not turning up to vote. It was enough for Lukashenko in Belarus to promise to deal with corruption and rampant inflation that was a result of the old guard’s mismanagement to turn Belarus into an autocracy. In Hungary, the change of regime came after the Socialist leader was caught on tape saying he had been lying to voters. While in Romania, only 39% voted in the 2016 election. And in Bulgaria, around half of the voters stayed at home in the presidential election the same year.
In sum, both incompetent and corrupt past leaders and disengaged or disillusioned voters are part of the decline in a liberal democracy that we have seen in recent years. It is clearly time for policy makers that are interested in preserving liberal democracy in the region and elsewhere to think hard about how democracy can be saved from illiberal democrats. Part of the answer clearly will have to do with how voters can be engaged in the democratic process and take part in elections. It also involves defending free independent media and the thinkers and doers that contribute to the liberal democracy that we cherish. The question is if the young generation will find a Greta for democracy that can kick-start a new transition to liberal democracy in the region and around the world.
For those readers that want to participate more actively in this discussion and have a chance to be in Stockholm on November 12, SITE is organizing a conference on this theme which is open to the public. For more information on the conference, please visit SITE’s website (see here).
References
- Freedom house data downloaded on Oct 4, 2019, from https://freedomhouse.org/content/freedom-world-data-and-resources
- Freedom house methodological note available at https://freedomhouse.org/report/methodology-freedom-world-2018
- Polity IV project data downloaded on Oct 4, 2019, from http://www.systemicpeace.org/inscrdata.html
- Polity IV project manual available at http://www.systemicpeace.org/inscr/p4manualv2018.pdf
- V-Dem project data downloaded on Sept 24, 2019, from https://www.v-dem.net/en/data/data-version-9/
- Coppedge, Michael, John Gerring, Carl Henrik Knutsen, Staffan I. Lindberg, Jan Teorell, David Altman, Michael Bernhard, M. Steven Fish, Adam Glynn, Allen Hicken, Anna Lührmann, Kyle L. Marquardt, Kelly McMann, Pamela Paxton, Daniel Pemstein, Brigitte Seim, Rachel Sigman, Svend-Erik Skaaning, Jeffrey Staton, Steven Wilson, Agnes Cornell, Lisa Gastaldi, Haakon Gjerløw, Nina Ilchenko, Joshua Krusell, Laura Maxwell, Valeriya Mechkova, Juraj Medzihorsky, Josefine Pernes, Johannes von Römer, Natalia Stepanova, Aksel Sundström, Eitan Tzelgov, Yi-ting Wang, Tore Wig, and Daniel Ziblatt. 2019a. “V-Dem [Country-Year/Country-Date] Dataset v9”, Varieties of Democracy (V-Dem)
- Pemstein, Daniel, Kyle L. Marquardt, Eitan Tzelgov, Yi-ting Wang, Juraj Medzihorsky, Joshua Krusell, Farhad Miri, and Johannes von Römer. 2019b. “The V-Dem Measurement Model: Latent Variable Analysis for Cross-National and Cross-Temporal Expert-Coded Data”, V-Dem Working Paper No. 21. 4th edition. University of Gothenburg: Varieties of Democracy Institute.
Latvia Stumbling Towards Progressive Income Taxation: Episode II
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
Higher Competition in the Domestic Market – A Way to Boost Aggregate Productivity
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
- Benkovskis, Konstantins; 2015. “Misallocation of resources in Latvia: did anything change during the crisis?”, Latvijas Banka Working Paper No.5/2015.
- Benkovskis, Konstantins; and Olegs Tkacevs, 2015. “Everything you always wanted to know about Latvia’s service exporters (but were afraid to ask)”, Latvijas Banka Working Paper No.6/2015.
- Berthou, Antoine; Emmanuel Dhyne; Matteo Bugamelli; Ana-Maria Cazacu; Calin-Vlad Demian; Peter Harasztosi; Tibor Lalinsky; Jaanika Meriküll ; Filippo Oropallo; and Ana Cristina Soares, 2015. “Assessing European Firms’ Exports and Productivity Distributions: The CompNet Trade Module”, ECB Working Paper, No. 1788.
- Braukša, Ieva; and Ludmila Fadejeva, 2016. “Internal labour market mobility in 2005–2014 in Latvia: the micro data approach”, Baltic Journal of Economics, 16(2), 152–174.
- Dias, Daniel A.; Carlos Robalo Marques; and Christine Richmond, 2015. “Misallocation and Productivity in the Lead Up to the Eurozone Crisis“, International Finance Discussion Papers 1146.
- Fadejeva, Ludmila; and Olegs Krasnopjorovs, 2015. “Labour Market Adjustment during 2008–2013 in Latvia: Firm Level Evidence”, Latvijas Banka Working Paper, No. 2/2015.
- Hsieh, Chang-Tai; and Peter J. Klenow, 2009. “Misallocation and manufacturing TFP in China and India“, The Quarterly Journal of Economics, 124(4), 1403–1448.