Tag: agriculture

EU Accession and Sustainability Challenges for Ukraine’s Agricultural Sector

Posted on November 18, 2024 | Policy Brief

Combine harvester in a Ukrainian wheat field symbolizing EU accession impacts on agriculture.

Recently the EU opened accession negotiations for Ukraine. Apart from the trade benefits of having access to a large and wealthy EU market, Ukraine’s agricultural producers in particular, will have to comply with and implement a complex and demanding EU acquis in agriculture. Together with the Common Agricultural Policy, this includes regulation of markets and standards in farming practices, animal and plant health, food safety, and environmental and animal welfare. The potential additional compliance costs from EU accession may undercut Ukraine’s agricultural competitiveness and supply growth, crucial for feeding a growing population. However, in this policy brief, we show that these costs are not critical and that there is a potential for agricultural producers to simultaneously increase their output and contract harmful environmental impacts, which in turn can compensate for the additional compliance costs.

Introduction

The European Council granted Ukraine candidate status in June 2022 and eventually opened accession negotiations in December 2023. For the Ukrainian agricultural sector, an EU membership would bring trade benefits from having access to a large and wealthy EU market. At the same time, Ukraine would have to comply with a complex and demanding EU Acquis in agriculture (hereafter called EU agricultural acquis). This, together with the EU Common Agricultural Policy (CAP), includes regulation of markets and standards in the areas of farming practices, animal and plant health, food safety, and environmental and animal welfare (Nivievskyi, 2024).

Complying with these regulations would entail additional costs for agricultural producers, raising concerns about the comparative advantage of Ukrainian agriculture. If these effects are strong enough, it could, in turn, hamper Ukraine’s agricultural supplies growth, crucial for feeding a growing global population.

While the evidence on the expected compliance costs is very scarce (see e.g. EU Commission, 2014), it shows they would be in the range of up to an additional 10 percent of the total costs. This cost increase, however, does not seem to ruin Ukraine’s comparative advantage in agriculture. Moreover, in this policy brief, we demonstrate that producers of grains and oilseeds in Ukraine have the potential to improve their efficiency by increasing their output by almost 20 percent and simultaneously contracting harmful environmental impacts by 16 percent. Such improvements can compensate for additional EU agricultural acquis compliance costs for Ukraine’s agricultural producers.

Relevance

Ukraine’s agricultural sector plays a key role domestically and internationally. It is noticeably dominated by crops, mainly by highly competitive grains and oilseeds. Agriculture alone accounts for about 10 percent of Ukraine’s GDP, but together with upstream (e.g. agricultural machinery) and downstream (e.g. food processing) industries, the entire agri-food sector’s share amounts to roughly 20 percent of GDP. The agri-food sector accounted for 60 percent of Ukraine’s total exports in 2023 with Ukraine’s shares in global corn and wheat trade reaching almost 20 and 10 percent, respectively.

At the same time, agriculture is among the top five sectors of the Ukrainian economy contributing to Nitruos Oxide (N2O) emissions in the country (SSSU, 2018). Since it generates not only desirable outputs but also environmentally undesirable ones (such as GHG emissions, pollution from applied chemical fertilizers and pesticides etc.), the negative outputs should be both considered in the assessment of the sector’s performance.

The existing empirical literature places the main focus on the economic aspects of the agricultural sector’s performance in Ukraine, more specifically on technical efficiency and total factor productivity. A recently published study (Halytsia, Vrachioli, Nivievskyi, Sauer, 2024) we undertake the first attempt to incorporate undesirable outputs of agricultural production in the analysis of Ukrainian agricultural producers’ efficiency and provide empirical evidence on how they perform from a combined economic and environmental perspective. This policy brief summarizes the study’s results.

Data and Methodology

To estimate the environmentally adjusted efficiency of crop producers, we use farm-level accounting data from 2017-2019, collected by the State Statistics Service of Ukraine. The analysis is conducted for cereals (including wheat, barley, maize and others) and sunflower production since they are the major crops in terms of sowing land and output shares and given their importance for Ukrainian agricultural export.

To account for both desirable and undesirable outputs of crop production (environmental bads in our study are N2O emissions originating from the usage of mineral fertilizers and CO2 emissions from fuels’ consumption), the production technology is formalized in the form of a hyperbolic distance function. This gives the maximum linear expansion of a desirable output vector and contraction of an undesirable output vector for a given input vector. Parametric estimation (deploying a so-called stochastic frontier model) of the distance function yielded hyperbolic efficiency estimates that reflect the producers’ ability to expand good outputs and simultaneously contract environmentally undesirable ones to achieve maximum environmentally adjusted economic efficiency.

Empirical Results

The results from the econometric analysis reveal that the average environmentally adjusted economic efficiency estimate for crop producers in Ukraine is 0.84 (efficiency estimates are bounded between 0 and 1). This suggests that, on average, producers of cereals and sunflowers in Ukraine can improve their production results by increasing crop output by 19 percent (1/0.84 = 1.19) while simultaneously contracting undesirable output by 16 percent (1–0.84 = 0.16) in order to be fully efficient, i.e. have their output level on the frontier of the production technology (Figure 1).

The obtained environmentally adjusted economic efficiency level is fairly comparable to the efficiency values estimated in empirical studies for crop producers in other Eastern European countries, more specifically Poland (Gołaś et al, 2020; Stępień et al., 2021).

Figure 1. Graphic synthesis of the study’s findings

Source: Authors’ presentation.

Policy Implications and Recommendations

Performance Improvement

The results from the empirical analysis show that there is room for Ukrainian crop farmers to improve their environmental and economic performance. The following policy interventions can be helpful in facilitating this improvement:

  • establishing clear standards for the quality of chemical fertilizers, promoting organic ones and robust agrochemicals management and monitoring systems
  • promoting the adoption of climate-smart agricultural technologies, such as, for instance, fertigation (which can be especially effective in the steppe agro-climatic zone where most Ukrainian crop production is concentrated and which is noticeably affected by changing climatic conditions)
  • governmental programs for energy saving in agriculture to help reduce the amount of farm CO2 emissions.

Implementation of these measures can contribute to closing the efficiency gap, bring more sustainable agricultural production growth and help farmers compensate for the anticipated costs of EU legislation compliance regarding environment, animal welfare, and food safety.  The latter, in turn, entails not only costs but also a number of benefits. Potential benefits from implementing environmental regulations are, for instance, input savings ( e.g. in fertilizer or pesticide costs), additional revenues (higher prices and increased consumer demand for agricultural products produced sustainably) and extension programs financed through public funds (Mettepenningen et al., 2009).

Data Collection Improvement

Key limitations of this study stem largely from issues related to data availability. More specifically, there is no data available on organic fertilizer application, specification of the types of used pesticides, or details on farm characteristics (such as farm economic size, land type, environmental subsidies, etc.). These data would enable a robust and comprehensive estimation of the environmentally adjusted economic efficiency of agricultural producers, accounting for a broader range of undesirable outputs and incorporating determinants of inefficiency into the analysis.

Currently, the State Statistics Service of Ukraine’s annual statistical survey forms do not contain questions which enable the collection of the above mentioned data. Enhancing farm-level data collection will be necessary to align Ukrainian statistical databases with Eurostat, given Ukraine’s candidate status for EU membership.

The importance of collecting data on farms’ environmental performance is supported by the ongoing transition in the EU from a farm accountancy data network to a farm sustainability data network, which aims to collect rich microeconomic data not only on farms’ income and business activities but also information on their environmental and social sustainability performance.

Conclusion

Over the two decades prior to Russia’s unprovoked full-scale invasion, Ukraine developed into an increasingly important global supplier of staple food.

In this policy brief, we quantify the improvement potential for the performance of crop producers in Ukraine from both economic and environmental perspectives and highlight that potential efficiency improvement could compensate for the additional EU agricultural acquis compliance costs that Ukraine’s agricultural producers are expected to face upon Ukraine becoming a full EU member.

Acknowledgment

This policy brief is based on the academic article Assessing the Environmental Performance of Agricultural Production Using a Parametric Approach: An Application for Crop Producers in Ukraine by Olha Halytsia, Maria Vrachioli, Oleg Nivievskyi and Johannes Sauer, published in Eastern European Economics.

References

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

Can Farmland Market Liberalization Help Ukraine in its Reconstruction and Recovery?

Posted on March 20, 2024 | Policy Brief

20240319 Farmland Market Liberalization Ukraine Image 01

The Russian full-scale invasion of Ukraine has inflicted massive damages and losses on Ukraine, already amounting to more than 2.5 times Ukraine’s 2023 GDP. Despite substantial and continuing international political and financial support to help Ukraine in its recovery and reconstruction, it is becoming increasingly clear that it will need to mobilize its own resources and private financing as well – not just for the country’s reconstruction but also for its long-term development. From a government perspective, it is important for Ukraine to leverage scarce public and donor resources and to undertake necessary reforms to facilitate and crowd in private financing. Farmland market liberalization is one of the key reforms in this respect. Its scale, with farmland accounting for more than 70 percent of Ukraine’s territory, and capacity for private financing generation for agriculture and rural areas is, however, often underestimated.  

An Unbearable War Toll and the Need for Private Financing

The raging Russian war on Ukraine enters its third year, imposing an immense toll in terms of human life, economic stability, and regional security. About 20 percent of Ukraine’s territory has been occupied. More than 10 million Ukrainians have left their homes, including 6.45 million refugees that have resettled across Europe (UNHCR, 2024). Ukraine’s military casualties are reported to be approaching 200,000 (The New York Times, 2023) and at least 10,000 civilians have been killed (United Nations, 2023). Ukraine’s GDP plunged by 30 percent in 2022, and the documented total damages to Ukraine’s economy have reached US$ 155 billion, as of January 2024 (KSE, 2024). Similarly, economic losses amount to around US$ 500 billion (as of December 2023). At the same time Ukraine’s reconstruction and recovery needs are estimated at about US$ 486 billion (World Bank, 2024). This immense number make up more than 2.5 times Ukraine’s 2023 GDP.

While there is a substantial and continuing international political and financial support for Ukraine’s defense, recovery, and reconstruction, this will not be enough (World Bank, 2023). Ukraine needs to mobilize its own resources and private financing, not just for its reconstruction but also for its long-term development. The Ukrainian government must leverage scarce public and donor resources and undertake necessary reforms to facilitate and crowd in private investments. One of the crucial reforms in this regard is the ongoing liberalization of the farmland market. The scale of its impact and capacity to generate private financing for agriculture and rural areas is frequently undervalued.

Ukraine’s Farmland Market and Reform

Almost 71 percent of Ukraine’s territory (or 42.7 million ha, including occupied territories) is farmland and 33 million ha is arable. This is far more than in the largest countries in the EU. Ukraine also has one-third of the world’s most fertile black soils. This resource has however been heavily underutilized for agricultural and overall economic development (KSE, 2021). Over the last two decades, Ukraine has turned into an increasingly important global supplier of staple foods (von Cramon-Taubadel and Nivievskyi, 2023), but this has largely happened without a full-fledged farmland market in Ukraine capable of facilitating even further agricultural productivity growth.

The farmland sales market was virtually non-existent for over three decades, instead rental transactions dominated. The farmland sales market began operating only in July 2021, and in a very limited format. Only individuals could purchase farmland plots and with a 100-ha cap per person. The minimum price was set at the normative monetary land value, and tenants had pre-emptive purchase rights while foreigners and legal entities were excluded; state and communal farmland remained under the 2001 sales ban. The farmland sales market opening was part of a large-scale land reform to support an efficient and transparent farmland market. This included a legislation package aimed at preventing land raiding, decentralizing land management, introducing electronic land auctions, establishing tools for land planning and use, creating a national infrastructure for geospatial data, establishing institutions for supporting small scale farmers, and empowering small scale farmers capacity to compete for land (KSE, 2021).

In general, there are two broad benefits of sales and lease transactions. First, the farmland market, via transactions, sorts out more efficient farms from less efficient ones, thus increasing the overall sector value added. Another important benefit, specifically linked to the farmland sales market, is that a functioning farmland sales market makes farmland a collateral which can generate productive investments in increased agricultural and non-agricultural productivity growth (Deininger and Nivievskyi, 2019).

Early Reform Outcomes

Almost two out of the first two and a half years of the reform phase unfolded amidst the profound shock from Russia’s full-scale invasion of Ukraine. Following this, nearly 20 percent of Ukraine’s farmland has been occupied (Mkrtchian and Mueller, 2024), almost a third of the agricultural sector has been ruined – the total damages and losses to the agricultural sector amount to US$ 80 billion (Neyter at al., 2024). As a result, a very restrictive first-phase format of the market, on top of the war challenges, effectively limited the expected benefits of the market liberalization.

The war has put a sizable drag on the farm-land sales market development, effectively slashing the transacted volume almost by half (see Figure 1).

Figure 1. Cumulative market transactions and the effect of the war.

Source: Nivievskyi and Neyter, 2024.

Overall, about 1.1 percent of total farmland area, or about 1.3 percent of Ukraine’s total controlled farmland (equivalent of 200,000 sales transactions or 444,300 ha) has been traded since the opening of the market. Regionally, the outcome is quite diverse (see Figure 2).

This is nonetheless an encouraging outcome as it is quite comparable to developed countries benchmarks where, on average, roughly 1 percent (and up to 5 percent) of the total agricultural land area is transacted annually (Nivievskyi et al., 2016). Another important outcome is that the transacted farmland has remained in agricultural production.

Farmland price development is also positive, especially for commercial farmland (see Figure 3). Since the commencement of the farmland sales market in Ukraine, the capitalization has increased by US$ 5.5 billion (KSE Agrocenter, 2024).

In fact, farmland market capitalization might be even greater. There are indications that the actual market price should be much higher, on average, than the officially registered one, as transacting parties may try and evade fees and taxes (Nivievskyi and Neyter, 2024).

Figure 2. Transacted area as share of total oblast (administrative region) area.

Source: The Center for Food and Land Use Research at Kyiv School of Economics (KSE Agrocenter), 2024.

Continued Farmland Market Liberalization and Associated Expectations

As of January 1, 2024, legal entities gained the right to acquire farmland that had, from 2001, been under sales ban. Also, in this second stage, the farmland accumulation cap per beneficiary increased to 10,000 hectares. Other restrictions remain, including that legal entities with a foreign beneficiary still cannot purchase farmland.

The first results of the second stage are premature, and firm conclusions cannot be drawn, yet the preliminary results are quite encouraging. The new market participants have already increased the volume of transactions and corresponding price by 13 percent, on average (see Figure 3).

Figure 3. Average farmland prices, in thousands UAH.

Source: KSE Agrocenter (2024). Note: Demonstration and estimations are based on the State GeoCadaster Data.

Another encouraging result highlights that legal entities bring further transparency into the market. For half of the transactions involving individuals, the sales price did not exceed the minimum price by more than 1.5 percent, while in half of the farmland transactions with legal entities, the price exceeded the minimum one by more than 44 percent.

These early results provide insight into the market’s direction and the associated benefits. The expected economic benefits from liberalizing the farmland market for legal entities could amount to an annual increase of 1-2.7 percent of GDP over the next three years.  The scale depends on many factors, including the availability of financing and financial support for small farmers (KSE Agrocenter, 2023).

Rural and agricultural financing is of particular interest as land is generally considered a high-quality collateral which could be utilized to attract loans and investments. This is particularly important during the current wartime period, as agricultural producers are facing significant collateral damage and severe financial difficulties for the third consecutive year. Currently, despite its potential, only a meager share of all farming loans is secured by farmland – far below global benchmarks.

Under current registered farmland prices, the total farmland market capitalization is equivalent to roughly US$ 35.5 billion. This could potentially generate an additional US$ 12.4 billion of loans (under the current low liquidity risk ratio of 0.35), already much greater than the current agricultural debt of about US$ 3.5 billion. Adding legal entities to the pool of farmland buyers (as of January 2024), is expected to increase farmland prices by an additional 40 percent. Thus, the farmland market will grow to almost US$ 50 billion, and the volume of land-secured financing could amount to US$ 17.5 billion. Further liberalization of the farmland market, such as a strengthening of its transparency, boosting the market liquidity, and accumulating necessary market statistics, may allow the National Bank of Ukraine to reconsider the liquidity risk ratio for farmland – potentially considering it as collateral similar to other types of real-estate (see the National Bank of Ukraine Resolution #351, June 30, 2016). A liquidity risk ratio at the level of developed countries (0.6-0.8) could further increase the volume of potential land-secured financing available to agriculture and rural areas/landowners to at least US$ 35 billion. This would, in turn, close the more than US$ 20 billion current financing gap for agricultural reconstruction, recovery and development. It would also contribute to Ukraine’s nearly US$ 500 billion reconstruction and recovery needs.

Further significant strides toward liberalizing Ukraine’s farmland sales market are anticipated as part of the country’s journey towards EU membership (European Commission, 2024), aligning with Chapter 4 ‘Free Movement of Capital’. Specifically, this pertains to allowing foreigners (EU citizens and legal entities) the right to purchase Ukrainian farmland (Nivievskyi and Neyter, 2024).

Conclusion

Russia’s full-scale invasion of Ukraine have inflicted massive damages and losses to Ukraine, already amounting to more than 2.5 times Ukraine’s 2023 GDP. The recently estimated reconstruction and recovery needs measure at nearly US$ 500 billion. This is an unbearable burden for Ukraine alone. Despite substantial and continuing support from international partners and donors, Ukraine will need to heavily draw on its own resources and capacity to generate private financing, not just for the country’s reconstruction, but also for its long-term development. It is therefore essential, from the Ukrainians government’s perspective, to focus on necessary reforms and optimize policy decisions to leverage the scarce public and donor resources and facilitate and crowd in private investments. Continued farmland market liberalization is one such critical reform, providing hope to generate substantial private investment in the agricultural sector and rural areas.

The size of the farmland market is immense (with farmland accounting for more than 70 percent of Ukraine’s territory). The first two years following the opening of the farmland sales market demonstrate a substantial potential for private financing generation for agriculture and rural areas. The results from regular market monitoring and the early findings, as discussed above, suggest that further farmland market liberalization and increased transparency could generate about US$ 35 billion of financing for agricultural producers and rural areas/landowners. That could, in turn, close the current agricultural financing gap of more than US$ 20 billion for rebuilding and recovery, as well as partially close the nearly US$ 500 billion financing gap for Ukraine’s overall reconstruction and recovery. The expected economic benefits from liberalizing the farmland market for legal entities are estimated at 1-2.7 percent of GDP annually, over the next three years. A further liberalization of the farmland market, and a step towards EU membership, would include granting foreigners (EU citizens and legal entities) the right to buy Ukrainian farmland – expected to bring even further benefits.

References

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

Land Market and a Pre-emptive Right in Farmland Sales

Posted on October 25, 2021 | Policy Brief

20211025 Land Market Image 01

After more than 20 years of a land sales ban, Ukraine finally opened its farmland market on July 1st, 2021. A design of the land market contains a pre-emptive right to buy the land for the farmland tenants. In this study, we model the effect of this pre-emptive right. Following the approach of Walker (1999), we use a theoretical model with three players – landowner, potential buyer, and the tenant – to model outcomes of the land transactions with and without the pre-emptive right. To empirically estimate the effect of the pre-emptive right, we use farm-level data to derive farmers’ maximum willingness to pay and the minimum price that landowners are willing to accept. The introduction of the pre-emptive right decreases the land price and increases the tenant’s chances of winning as well as his surplus, at the cost of a potential buyer and the landowner. The introduction of the pre-emptive right also leads to inefficient distribution and deadweight losses to the economy.

Introduction

After more than 20 years of a land sales ban, Ukraine finally opened its farmland market on July 1st, 2021. The moratorium on the sales of agricultural land in Ukraine covered of 96% of the country’s farmland market (or 66% of its entire territory).

The critical element of the newly opened Ukrainian farmland market design is the pre-emption right (right of the first refusal, RoFR) that is granted to the current tenant of land plots. By applying their pre-emptive right, tenants can purchase the land at the highest price the landowner could get on the market. On top of that, this right is transferable, meaning that the tenant could sell the right to the interested party. In this brief, we model the consequences of the pre-emptive right introduction in Ukraine.

Farmland Market in Ukraine

The moratorium on farmland sales that was in place for the last 20 years created a substantial distortion on the farmland market. It led to the situation where large companies predominantly cultivate the rented land, with the average share of leased land in the land bank for corporate farms in Ukraine approaching 99% (Graubner et al., 2021). Another noticeable trait of the farmland market in Ukraine is significant inequality in Ukrainian farms’ land banks. Based on the statistical forms 50AG, 29AG, and 2farm, our calculations show that the GINI index for the allocation of cultivated land across farms in Ukraine is 86%, indicating an extreme degree of inequality. As we can see from Table 1 – the top 10% of farms operate on 75% of all cultivated farmland in Ukraine.  On the other side of the spectrum, 49% of the smallest farms in Ukraine operate on only 2% of the cultivated farmland and rent only 0,3% of all rented farmland.

Table 1. Ukrainian farmland market structure 

Source – own calculations based on the statistical forms 50AG, 29AG, 2farm for the year 2016.

Therefore, in our analysis, we break a sample of Ukrainian farms into five categories with respect to their size.

Framework

To model the effect of the pre-emptive right, we will use the approach proposed by Walker (1999) using farm-level data. Thus, this study compares two scenarios – with the pre-emptive right (right of the first refusal, RoFR) and without the pre-emptive right in place. We assume that there are only three sides to each transaction – the seller (landowner), the prospective buyer, and the tenant, to whom the pre-emptive right is granted. Throughout this brief, we assume that there are no transaction costs involved.

Scenario 1. No Pre-emptive Right

In the no-RoFR scenario, the prospective buyer offers the landowner a price that the seller is willing to accept. The seller now has two options: either accept and get the offered price or reach the tenant and propose to outbid this offer. The option of reaching a tenant is more attractive since, in a worst-case scenario, if the tenant’s valuation – i.e., the maximum price the tenant is willing to pay for the land plot – is lower than the offered price, the tenant would simply not respond to this offer, and the landlord still gets the offered price.

On the other hand, if the tenant’s valuation is higher than the offered price, he has a strong incentive to make the counteroffer and start a bidding process. Both the tenant and the prospective buyer are incentivized to make a counteroffer up until the point where the offer’s value reaches their respective valuation. Thus, the smallest valuation between those of the tenant and prospective buyer would be the final transaction price.

Scenario 2. A Tenant Has the Pre-emptive Right

In this scenario, the tenant does not need to increase the price in his counteroffer if the third-party buyer’s offer is lower than the tenant’s valuation. The tenant could execute his pre-emptive right and buy the plot at the third-party buyer’s proposed price. Therefore, the outside buyer will change his approach to the initial offer. If the offer he makes is “too low”, he loses the chance of buying this plot since the tenant would exercise his pre-emptive right. If the offer is “too high,” he misses the profit he would make by making a lower offer.

In such circumstances, the transaction price will be given by the third-party buyer’s offer that maximizes his expected profit. The latter, in turn, depends on the probability of the tenant exercising his preemptive right, the third-party buyer’s own valuation, and the price he offers to the landlord. The probability of the tenant exercising the offer is the probability that the tenant’s valuation exceeds the offered price. It depends on the tenant’s farm size category and on the offer itself and can be calculated based on the distribution of valuations.

Empirical Approach

Our empirical analysis considers a (hypothetical) situation of a third-party buyer coming to the landowner, whose land is rented to another farmer, with the offer to buy a one-hectare plot. We assume that the offer exceeds the landowner’s minimum price that a landowner is willing to accept (WTA). The landowner’s WTA is proxied by the current rental price the landlord gets multiplied by the capitalization rate, set to 20 for all three sides of the transaction. The farmers’ valuations are estimated based on their net profit per hectare. We use the farm-level data to compute the average net profit per hectare needed for valuations estimation and the average rental price per hectare for the WTA estimation. This data was collected by the State Statistics Service of Ukraine through statistical questionnaires called 50AG, 29AG, and 2farm for the year 2016 and covers 39,297 farms. The descriptive statistics of the data are presented in table 2.

Table 2. Descriptive statistics

Source: own calculations based on the statistical forms 50AG, 29AG, 2farm for the year 2016.

We construct a set of potential buyers for each farm that operates on rented land based on the 10-km threshold distance between the tenant and third-party buyer. We end up with a sample of 764760 pairs of tenants and potential third-party buyers. We drop all pairs where third-party buyers cannot make an offer landlord is willing to accept. Therefore, only a sample of 291506 observations of tenant – prospective buyer pairs is used for the analysis. Importantly, for large and ultra-large farms, the share of observations that would attempt a transaction is 70% and 69% correspondingly. On the lower side of the size spectrum, this share is noticeably lower. For the group of small third-party buyers, the buyer would attempt the transaction only in 42% of cases. The most excluded from the farmland sales market category are ultra-small farms as they would only attempt the transaction in 25% of all cases.

Results

Our findings suggest that the effect of the pre-emptive right on the land price is twofold. On the one hand, in 55% of cases – the RoFR price is higher than the (modelled auction) price in the absence of a preemptive right. However, the median price differences in these cases are just 0,7% of the auction price. At the same time, for the cases where the auction price is higher than the price with the RoFR, it exceeds the RoFR price, on average, by 83%, with a median value of 66%. As a result, if we compare the expected prices, the expected prices under the RoFR are significantly lower than the auction prices. There are also differences between different farm size categories of the third-party buyer – the larger the buyer is, the higher the transaction price would be regardless of the RoFR. In the scenario without the RoFR, the average transaction price for ultra-small farms would be $1259 per hectare. While for the ultra-large farm as the third-party buyer, the transaction price would be $1647. With the pre-emptive right granted to the tenant, the transaction prices would be $977 and $1313 correspondingly.

The pre-emptive right also increases the probability of the tenant acquiring the land. The most noticeable effect is for ultra-small and small farms – if an outside buyer attempts the transaction, their chances of purchasing the land increase from 12% to 28% and from 23% to 45%, respectively. The probability increase for the larger tenants persists, but percentage-wise it is smaller – their probability of purchasing the land due to the granted pre-emptive right increases from 42-45% to 65-66%.

The pre-emptive right also redistributes the surplus from the transaction. Measuring the surplus as the difference between the valuation and the buyer’s actual purchase price, we can conclude that the third party’s surplus decreased due to the RoFR introduction. The tenant’s surplus, on the other hand, increases. In the case of RoFR introduction, the percentage increase in the tenant’s surplus is larger for the ultra-small and small farmers, from 5% to 13% and from 10% to 23% of the tenant’s valuation, respectively. For larger farms, albeit the surplus’ increase is larger in absolute terms, percentage-wise, it is smaller than for their smaller counterparts. Their average surplus increased from 18-20% to 37-38% of the tenant’s valuation. For the third-party buyers, the percentage-wise decrease is more or less the same, regardless of their farm size. Their surpluses, on average, shrink by 23-27% depending on the size of the farm.

We also estimated the effect of the pre-emptive right on the joint surplus of the landlord and the tenant. The effect of the pre-emptive right on their joint surplus is positive regardless of the size category of the tenant. The largest increase of the joint surplus, percentage-wise, is observed for the small-sized farms as a tenant. In this case, the average joint surplus increased by 5%, translating into an $87 increase in the joint surplus. In absolute terms, the highest increase is for medium-sized farms as a tenant – $108 increase in the surplus or 4.5% of their original joint surplus.

The pre-emptive right also leads to inefficient allocations when the land is acquired by a lower valuation party, resulting in deadweight losses. Inefficient allocation is observed in 19% of all observations. The deadweight losses generated by the introduction of the ROFR are statistically significant (with the t-value equal to 195) and average 233 USD per hectare.

Conclusions

In this brief, we suggest a theoretical and analytical approach to calculate the impact of the pre-emptive right in farmland sales. Our analysis offers a range of important findings. First, small and medium-sized farms are almost entirely excluded from the farmland market. While more than two-thirds of the medium, large or ultra-large farms can afford to buy a nearby parcel, based on their profitability – for ultra-small farms, which have a land bank of under 50 hectares – this share is equal to just 25%. The introduction of the pre-emptive right granted to the current tenant may exaggerate this problem. The reason is that most of the rented land is already controlled by large and ultra-large companies. At the same time, the pre-emptive right increases the tenant’s probability of winning and its surplus at the expense of the landowner and outside buyer.

On the other hand, the pre-emptive right increases the joint surplus of the tenant and the landowner. Therefore, if the pre-emptive right would be a voluntaristic clause in the contract, rather than a right granted to all tenants by the government, it creates an incentive to include the pre-emptive right in the rental agreement with the price of this right negotiated between the landlord and the tenant.

Summing up, the pre-emptive right, as a policy instrument, has its costs. It leads to inefficient distribution and deadweight losses. In view of this, as much as the recent farm market reform in Ukraine is a clear step towards a market economy, the design of the land market should be taken with a grain of salt.

References

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

Agricultural Exports and the DCFTA: A Perspective from Georgia

Posted on February 18, 2019 | Policy Brief

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On June 27, 2014, Georgia and the EU signed an Association Agreement (AA) and its integral part – the Deep and Comprehensive Free Trade Area (DCFTA). In this policy brief, we discuss the changes and analyze the agricultural exports statistics of Georgia since 2014. Furthermore, we will provide the recommendations to capitalize on the opportunities that the DCFTA offers to Georgia.

Georgia is a traditional agrarian country, where agriculture constitutes an important part of the economy. 36.6% of the country’s territory are agricultural lands and 48.2% of the Georgian population live in villages. Although 55% of population are employed in agriculture, Georgia’s agriculture accounts for only 15.8% of its GDP (Geostat, 2019). Agricultural exports constitute an important part of Georgia’s economy, accounting for about 25-30% of total exports.

On June 27, 2014, Georgia and the EU signed an Association Agreement (AA) and its integral part, the Deep and Comprehensive Free Trade Area (DCFTA). On July 1st, 2016, the DCFTA fully entered into force. The DCFTA aims to create a stable and growth-oriented policy framework that will enhance competitiveness and facilitate new opportunities for trade. The DCFTA widens the list of products covered by the Generalized System of Preferences+ (GSP+) and sets zero tariffs on all food categories (only garlic is under quota), including potentially interesting products for Georgian exports – wine, cheese, berries, hazelnuts, etc. (Economic Policy Research Center, 2014).

As July 2018 marked only two years since the implementation of the DCFTA between Georgia and EU, valuable conclusions on its impact cannot be formulated yet. In this policy brief, we will give an overview of Georgia’s agricultural trade statistics, particularly, we will focus on agricultural exports and provide recommendations for capitalizing on opportunities offered by the DCFTA.

Georgia’s agricultural trade

Despite its potential and natural resources, Georgia is a net importer of agricultural products. In 2018, Georgia’s agricultural exports increased by 23.2% (181 million USD), while the respective imports grew by only 15.5% (179 million USD) compared to 2017. Therefore, the trade balance (the difference between exports and imports) remained almost unchanged at (-394) million USD (Figure 1).

Figure 1: Georgia’s Agricultural Trade (2014-2018)

Source: Geostat, 2019

Out of the sharp increase in agricultural exports, 100 million USD are attributed to tobacco and cigars. Since Georgia cultivates very little tobacco, the growth was instigated mostly from the import, slight processing and re-export of tobacco products. Consequently, the export of tobacco and cigars increased by 240% in 2018, and it currently holds second place (after wine) in Georgia’s total food and agricultural exports. It should be mentioned that wine exports contributed to 26 million USD in export growth.

Over the last five-year period, the top export countries for Georgia were mainly neighboring counties (Azerbaijan, Russia, Armenia, Turkey); for imports, we see the same neighboring countries as well as China and Ukraine. Observing the trade statistics over the years, 45% of Georgia’s agricultural exports were destined for markets in countries of the former Soviet Union, so-called Commonwealth of Independent States (CIS), while the EU’s share in Georgia’s total agricultural exports was 24%.

Trade relationships between Georgia and the EU

The EU is one of Georgia’s largest trade partners. The EU’s share of total Georgian imports was 28% in 2018, and for exports, 24%. Total exports have been more or less stable since 2014, except for 2016, when an 11% decrease was observed (Figure 2). Specifically, for agriculture, in 2017, the EU’s share of Georgian imports was 22%, and its share of exports was 19%. During the same period, the top export products were hazelnuts (shelled), spirits obtained by distilling grape wine or grape marc, wine, mineral and aerated waters and jams, jellies, marmalades, purées or pastes of fruit.

Figure 2: Total and Agricultural Exports to the EU (2014-2018)

Source: Geostat, MoF, 2019

In 2015 (before the full enforcement of the DCFTA), Georgia’s agricultural exports to EU countries (including the United Kingdom) increased by 20% compared to the previous year. This positive trend remained in 2016, when the same indicator increased by 5%. In 2017, which was quite a bad year in terms of harvest in Georgia, we observed a 38% decrease in the country’s agricultural export to the EU (Figure 2). This decrease was mainly caused by a significant decrease (64%) in hazelnut exports during the same period. The reason for such a large decrease is that hazelnut production suffered from various fungal diseases due to unfavorable weather conditions in 2017. The Asian Stink Bug invasion worsened the situation, and in the end, hazelnut exports dropped dramatically in both value and quantity. In 2018, Georgia’s agricultural export in EU slightly increased by 6% compared to 2017.

Trade relationships between Georgia and CIS countries

It is interesting to observe agricultural trade within the same time period with CIS countries. In 2018, the CIS’ share of Georgian imports was 51%, and its share of exports was 60%. The top export products to CIS countries were wine, mineral and aerated waters, spirits obtained by distilling grape wine or grape marc, hazelnuts (shelled), and waters, including mineral and aerated, with added sugar, sweetener or flavor, for direct consumption as a beverage. As we can see in both EU and CIS countries, the top export products are more or less the same. However, the main export destination market for Georgian hazelnuts are EU countries, but wine is mostly exported to the CIS countries.

Figure 3: Agricultural Exports to CIS Countries (2014-2018)

Source: Geostat, MoF, 2019

Due to the worsened economic situation in CIS countries, Georgia’s agricultural exports to these countries decreased by 37% in 2015. Such a sharp decrease was mainly driven by a significant decrease in the export of alcoholic and non-alcoholic beverages, hazelnut, and live cattle. However, since 2015, Georgia’s agricultural exports to CIS countries have been increasing; we observed a slight 2% increase in the value of agricultural exports in 2016, while the same indicator was 37% in 2017 (Figure 3). That was mainly caused by the increased exports of alcoholic and non-alcoholic beverages (wine by 61%, spirits by 28%, mineral and aerated waters by 22%). In 2018, Georgia’s agricultural export in CIS countries increased by 12% compared to 2017.

Conclusion

Despite its potential and comparative advantage in agriculture, Georgia is still a net importer of agricultural products and has negative trade balance (-394 mn USD). Two years after the DCFTA came into force, it is challenging to know its impact on Georgia’s agricultural trade due to the insufficient passage of time since. Notwithstanding, we can formulate some conclusions from trade statistics. The diversity of the destinations for Georgia’s agricultural exports has not changed through the years. Georgia’s agricultural exports has increased to the EU, but at a quicker pace to CIS too. Furthermore, Georgia’s share of agricultural exports to CIS countries is still significant (60%).

While it is obvious that Georgia needs to diversify its agricultural export destination markets, there are several challenges facing small and medium size farmers and agricultural cooperatives in Georgia that are not specific to implementation of the DCFTA. As the previous regime (GSP+) with the EU already covered most products, the DCFTA did not represent a significant breakthrough. On the path to European integration, the biggest challenge for Georgia is to comply to non-tariff requirements such as food safety standards and SPS measures. The attention should be paid on providing consultations to farmers regarding certification processes and standards and better information sharing (e.g. developing online platforms).

In Georgia, agri-food value chains are not well-developed and lack coordination among different actors. In order to capitalize on opportunities offered by the DCFTA, government and private sector should work together to improve logistics infrastructure. There is a need for upgrading at every stage of export logistics: warehousing, processing, labeling, regional consolidation, final customer services. In this regard, there are high approximation costs for business that should be considered as long-term investment to modernize agriculture and improve food the safety system in the country. This would boost the export potential not only to the EU, but to other countries with similar requirements as well.

References

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

The Economics of Russian Import Substitution

Posted on December 5, 2016 | Policy Brief

FREE Network Policy Brief Image | The Economics of Russian Import Substitution

This policy brief discusses the economic mechanisms triggered by import substitution policies, associated losses and conditions that ensure positive economic effects. Numerical estimations of potential effects of Russian import substitution policies indicate a decline in GDP, decrease in output of unprotected sectors and consumers’ welfare losses. We conclude with a discussion of the role imports play in economic efficiency.

Import substitution: pro and contra

Two years after joining the WTO, in the new political reality, Russia began implementing a series of import substitution policies. Supported sectors range from agriculture and production of metal products, to computer equipment and special purpose vehicles. The potential economic effects of these policies are of substantial interest and importance both for researchers, policymakers and the general public. However, they have not yet been quantitatively assessed. This policy brief summarizes the results of a study of these effects conducted at CEFIR in 2016 (Volchkova and Turdyeva, 2016).

Import substitution can be implemented by a range of instruments aimed at creating preferential conditions for domestic producers of imported goods compared to foreign competitors. Barriers to trade are the most common and easily available policy tools. Trade barriers lead to price increase on domestic market relative to the world price of the good.

Domestic manufacturers in the protected industry enjoy higher prices on domestic market, thereby securing higher revenues at the same costs. The protected sector also is able to put into operation those capacities that were generating losses in the absence of protective measures. However, if the economy works at full employment in absence of import substitution, then in order to increase production in the protected sectors, factors should be reallocated there from the other sectors. As a result of the import-substituting policy, producers in unprotected sectors will decrease the scale of production, and some will exit the industry. That is, producers that were efficient enough before import substitution policies will be forced out by those that cannot compete at international prices. From the point of view of welfare economics, this maneuver is accompanied by a loss of economic efficiency.

Economic literature discusses several cases when import substitution can be justified, such as a presence of positive external effects from protected sectors to the economy; learning-by-doing effects in protected sectors; and an infant industry argument. All of these cases imply market failures in the absence of government intervention, leading to lower than socially optimal output of the sector in question. Then, government interventions aiming to increase output – such as import substitution – might bring additional welfare improvement to the economy. If any of these effects do take place then the gain brought by protected sectors may compensate for the loss by the unprotected. To validate any of these cases one needs to perform a thorough and independent analysis of the economy based on very detailed information.

Estimates of static and dynamic effects of import substitution

In order to illustrate the potential effects of import substitution policies in the current Russian situation, we use a static CGE model of the Russian Federation constructed at CEFIR.

Based on publicly available documents (Russian Government’s Decrees №2744-Р 29.12.2015 and № 2781-р 31.12.2015), we identify the sectors that are targeted by the import substitution policy: agriculture and four manufacturing sectors (metal production; machinery and equipment; cars; sea crafts, airplanes and spaceships).

To model the effects of import substitution, we calculate an ad valorem tariff equivalent, which ensures a 10% decline of the volume of import in each of five industries. In order to simulate proposed policy measures, we conduct six experiments: increase in import tariffs in each of five industries individually, and a comprehensive policy change with an increase in all five tariffs simultaneously.

If import substitution policy is implemented not by trade policy instruments but only through producer support measures then it will be accompanied only by changes in relative prices for producers while consumer prices will not be affected and will be determined solely by international prices. In this case, our estimates will represent an upper bound of possible consumers’ losses. Since the distortion of relative prices for producers do not depend on a particular instrument chosen to implement import substitution policy then the consequences for other sectors and for efficiency of the overall production will be the same under trade or domestic policy interventions.

Table 1 shows the results of our calculations. Columns (1) – (5) present the estimates of the effects of the import-substitution measures in the relevant sectors. Column (6) reports the results of the comprehensive policy reform.

Table 1. Consequences of the decline in imports by 10% in the protected sector (s).

  Agriculture Metals Machinery, and equipment Cars Sea crafts, airplanes and space ships Tariff change in all industries
(1) (2) (3) (4) (5) (6)
Ad valorem tariff equivalent, % 2.9 3.9 6.1 6.7 5.6
Change in
CPI, % 0.04 0.09 0.39 0.3 0.3 1.0
Protected sectors’ output, % 0.7 2.5 9.8 10.3 8.3 3.8
All other production, % -0.2 -0.4 -0.5 -0.2 -0.5 -2.3
GDP, % -0.002 -0.011 -0.023 -0.005 -0.018 -0.049
Welfare, % -0.015 -0.020 -0.074 -0.041 -0.080 -0.215

Source: Authors’ own estimation.

Our results illustrate the anticipated effect of import substitution policy in economy with full employment. The protected industries increase their output at the expense of other industries. An increase in economic inefficiency is reflected by a fall in GDP.

In order to capture dynamic effects of the proposed import substitution policy, we simulate an import tariff increase in a Solow-type growth model calibrated for the Russian economy. The proposed policies result in a deeper economic decline in 2016 than in the baseline scenario (-0.76% in the baseline scenario and -0.79% in the import substitution scenario), followed by somewhat faster growth in subsequent years due to a lower base. The aftermath of the import substitution policy is still visible in 2020: GDP growth in 2020 relative to 2015 in the baseline equals 2.4365%, while the import restriction in all targeted industries will reduce economic growth in a five-year term by 0.007 percentage points, to 2.4295%. The numbers correspond to the expected reduction in economic efficiency as a result of the import substitution measures.

While numbers in terms of GDP do not look particularly large, the annual losses in GDP in nominal figures correspond to $650 million in value added, which is roughly equivalent to 30,000 jobs lost in Russia due to import substitution. Besides, effect on growth adds to 5,000 more jobs lost over 5 years.

As we mentioned above these losses might potentially be justified by the positive external effect from an increased output of the protected industries on the rest of economy. To ensure this, the selection of industries for protection should have been done through independent expertise based on a thorough analysis of sectoral interaction over time. However, the way the economic policy is formulated in modern Russia, with heavy influence of lobbying groups and very little contribution from independent economic research, we can hardly expect that the industries targeted for import substitution satisfy the objective criteria of positive external effects.

Imports as drivers of competitiveness

Classical trade theory shows that imports are a major cause of gains from trade integration. Modern trade theory complements the classical mechanism by selection effects among heterogeneous firms when only the most productive firms are able to sell in foreign markets (Melitz , 2003).

Keeping in mind that a substantial part of manufacturing trade flows consists of intermediate products that are used as inputs in subsequent production (in the case of Russia, the share of intermediates in imports is more than 60%) then the above reasoning implies that the competitiveness of domestic production is determined, among other things, by the availability of cheap imports.

Numerous empirical studies for many countries confirmed that industries with a higher share of imported intermediate goods are more productive than industries with a lower share (Feenstra, Markusen, and Zeile, 1992). Recent studies, analyzing data at the level of individual firms (Bernard at al., 2012; Castro, Fernandes, and Farolec, 2015; Feng, Li, and Swenson, 2016), confirm that the effect takes place at firm level: firms importing more intermediate goods have higher productivity than firms importing less, other things being equal, which suggests that imports of intermediate goods is an important source for the growth of firms’ competitiveness.

A study conducted for Russian firms showed that labor productivity in Russian companies which import intermediate goods is 20% higher compared to similar firms not importing intermediates (Volchkova, 2016).

On this basis, we have every reason to believe that import is one of the sources of economic competitiveness that enhances effectiveness of the economy. Thus import substitution policies in the absence of objective information and a profound selection procedure for protected sectors, are harmful to the economy. In an open economy, the effect of the firms’ selection and the availability of cheap imports ensure growth of sectoral productivity, but productivity declines in “protected” sectors. That is, while our estimates above assess the direct negative impact on Russian economic output and welfare from inefficient reallocation of factors of production, the implementation of import substitution policies also puts the Russian economy in a disadvantaged position relative to more liberal economies on the international markets due to forgone competitiveness. This creates additional obstacles for Russia on its way to export diversification and sustainable growth.

References

  • Feenstra, Robert C, James R Markusen, and William Zeile. 1992. “Accounting for Growth with New Inputs: Theory and Evidence.” The American Economic Review 82 (2). American Economic Association: 415–21. http://www.jstor.org/stable/2117437.
  • Feng, Ling, Zhiyuan Li, and Deborah L. Swenson. 2016. “The Connection between Imported Intermediate Inputs and Exports: Evidence from Chinese Firms.” Journal of International Economics 101: 86–101. doi:10.1016/j.jinteco.2016.03.004.
  • Melitz, Marc J. 2003. “The Impact of Trade on Intra-Industry Reallocations and Aggregate Industry Productivity.” Econometrica 71 (6). Blackwell Publishing Ltd: 1695–1725. doi:10.1111/1468-0262.004
  • Pierola Castro, Martha D., Ana Margarida Fernandes, and Thomas Farolec. 2015. “The Role of Imports for Exporter Performance in Peru.”
  • Volchkova, Natalya A. 2016. “Prospects of the export diversification:” Dutch Disease “or the failures of economic policy?” in “Seven lean years: the Russian economy on the verge of structural changes: the round table materials” / ed. Rogov. -Moscow: Foundation “Liberal Mission” (in Russian)
  • Volchkova, Natalya A., and Natalia A. Turdyeva 2016, “Microeconomics of Russian import substitution”, Journal of New Economic Association, forthcoming (in Russian)

Did the Fertilizer Cartel Cause the Food Crisis?

Posted on March 23, 2015 | Policy Brief

Authors: Hinnerk Gnutzmann, Catholic University of Milan, and Piotr Spiewanowski, Polish Academy of Sciences.

Food prices escalated during the 2007/2008-food crisis and have remained at historically high levels since. We show that an international export cartel for fertilizers was an important driver of the crisis, explaining up to 60% of the price increase. While biofuel subsidies, high energy prices and financial speculation doubtlessly put stress on food markets, our findings suggest new avenues for policy in the fertilizer market to stabilize food markets.