Research

In my research, I employ economic theory and econometrics to improve and contribute to agricultural economics and trade literature. My most recent research delves into understanding big data and machine learning. Working on improving the gravity model and bringing more big data approaches into agricultural economics literature remains my central focus and motivates my plans for future research. 

My master's thesis, published in the Journal of Agricultural and Applied Economics, focuses on consumer food preference changes in Russia using provincial-level panel data on the consumption of seven food varieties and various supply shifters. The results show that consumers underwent a structural preference change from 2007 to 2014. The research was done using the Generalized Exact Affine Stone Index approach, which allowed me to evaluate price and income elasticities of demand more accurately. While I am passionate about consumer economics, during my Ph.D., I have been exploring a new area of interest: the gravity model of international trade. This change allowed me to express my interests in different ways.  

In the first chapter of my dissertation, published in the Journal of Agricultural Economics, I focus on understanding the determinants of dairy trade. Given the recent changes in the supply and demand of dairy products, many opportunities arise for exporting and importing countries. This paper examines determinants of dairy-product trade by applying the Poisson Pseudo-Maximum Likelihood (PPML) method to the structural gravity model using panel data on 49 exporting and 235 importing countries for 17 years (over 2000-2016). The gravity model is estimated using both interval data and dynamic analyses.  A key contribution of this paper is examining the effects of domestic subsidies on the dairy products trade. The outcomes confirm our hypothesis, revealing that domestic subsidies have a modest but positive impact on dairy-product trade across the various models. This result aligns with our expectations, as domestic subsidies are not expected to directly influence trade but rather facilitate producer investments in production and technological enhancements. Conversely, the results reveal no statistically significant effect of tariffs, while trade agreement memberships, market size factors, and government institutions also positively affect dairy-product trade. Results from the lag-policy analysis show that the impact of subsidies disappears after the second year of distribution. In contrast, for the lead-policy analysis, results suggest at least three years of anticipatory effects on domestic support. 

In my second chapter (job market paper), I introduce an innovative econometric approach known as 2-way Fixed Effects Distribution Regression (DR), alongside standard PPML methods, to offer a unique perspective on the gravity model. The DR model provides a rigorous approach for estimating heterogeneous effects across countries at various quantile levels, moving beyond conventional mean analysis. However, a limitation of the current DR model is that it can only accommodate cross-sectional data. As DR results are not directly comparable to PPML, DR provides a unique perspective in the trade literature on outcome variables, and the two methods complement each other. The PPML analysis utilized panel data for 25 years between 1995 and 2019 on bilateral trade flows of dairy products to examine the effects of sanitary and phytosanitary measures, technical trade barriers, trade agreements, customs unions, and friction variables (distance and shared languages, borders, and colonial history) on the dairy trade flows. However, for the cross-sectional DR analysis, I utilized 2019 data. This study's primary objective is to explore whether quantile analysis provides additional insights compared to mean analysis. Our hypothesis revolves around the notion that policy and friction variables have different effects on countries with different market sizes, as well as on developed and developing countries. Our findings confirmed our hypothesis. The countries that trade more (located on the upper tail of the distribution) are affected differently by different factors, such as policy factors and friction variables, than those that trade less (located on the lower tail of the distribution). Standard empirical trade models used in the literature cannot observe these heterogeneous effects, giving us a limited view of the potential effects of trade flows. 

In my third chapter, the main objective of this study is to analyze the impact of Producer Support Estimates (PSEs) on agricultural trade. To this end, I use counterfactual and machine learning analysis alongside the PPML models to examine the impact of these subsidies and other determinants on agricultural trade using panel data of 72 exporting and 256 importing countries for 20 years from 2000 to 2019. The analysis uses aggregated agricultural trade data to examine the impacts of aggregate and decomposed (commodity-specific and non-commodity-specific) domestic subsidies. I hypothesize a positive effect of PSEs on trade, as found in the first chapter. The results, however, offer a more nuanced perspective. While aggregate PSEs do not significantly affect agricultural trade, decomposing PSEs into commodity and non-commodity supports provides additional insights. The results indicate that the coefficients of commodity-specific supports are statistically insignificant. This may occur because the products that receive commodity-specific PSEs vary by country and are a subset of all agricultural commodities. This changing sub-set of commodities by country introduces substantial noise regarding the impact of these subsidies on aggregate trade. Therefore, this result suggests that the effects of commodity-specific PSEs need to be examined for individual commodities rather than aggregate agricultural trade (as is done in the first chapter). However, the coefficient of non-commodity-specific PSEs is positive and significant, confirming the hypothesis that subsidies increase exports. The next step is to study counterfactual effects, where subsidies are removed to evaluate the direct and indirect (i.e., third-party) impact on agricultural trade. Then, using machine learning approaches, I will allow the computer to help inform what factors determine trade, in contrast to making functional form assumptions and comparing counterfactual analyses using structural gravity versus machine learning.  

Besides my dissertation and international trade, I have made inroads into health economics. Specifically, we study the effects of tobacco control policies on tobacco consumption (the paper is under review in the American Journal of Agricultural Economics). We use the Smoothed Instrumental Variables Quantile Regression approach to address methodological and data limitations plaguing the previous literature. We find that heavy smokers are most affected by tobacco expenditures, while smoke-free laws are found to be less potent policy tools.  

I will continue developing and utilizing my expertise to address questions relevant to agricultural, consumer, and international economics. My future work includes developing novel theoretical and empirical econometric approaches to the gravity model building upon the DR model discussed. For example, the current DR model can only accommodate cross-sectional data. I plan on expanding the model to the panel data to apply the structural gravity model and address heterogeneity in trade data. Within the current DR framework, there are many existing research opportunities. Two such opportunities include examining the heterogeneous effects of imperfect competition in agricultural markets and policy variables (tariffs, free trade agreements, customs unions, etc.) for different commodities.  

Navigating the Complexities of Dairy Trade: A Comprehensive Trade Policy and Frictions Analysis Using PPML and DR Methods

Abstract: Given the complex nature of international trade, we explore the average and distributional effects of trade policy and friction variables across different trade values using both recently developed Poisson Pseudo Maximum Likelihood (PPML) and distribution regression (DR) methods to estimate gravity models. We study the impacts of sanitary and phytosanitary (SPS) measures, technical barriers to trade (TBT), tariffs, different trade agreements, customs unions, and friction variables, such as distance, common languages, contiguity, and colonial history on bilateral trade flows of dairy products for 242 exporter and 243 importer countries between 1995 and 2019. The results from PPML gravity analyses suggest that SPS measures reported to WTO negatively affect dairy trade, while TBT boosts trade. We also observe significant trade agreements' effects on dairy trade. We further enhance our analysis by separating intra-distance from international distance to examine how the separate effects compare to the combined distance effect. The DR results, using the counterfactual effects analysis, show heterogeneous effects for the policy and friction variables. For example, TBT has a moderately positive and heterogeneous impact on dairy trade flows, which is becoming particularly pronounced for the upper quantiles of trade flows. We also find that distance shows a strong negative heterogeneous impact across the entire distribution of dairy trade flows.

Chapter 1: Determinants of Dairy Trade: Do Subsidies Matter?

Abstract: Given the recent changes in the supply and demand of dairy products, many opportunities arise for exporting and importing countries. This paper examines determinants of dairy-product trade by applying the Poisson Pseudo-Maximum Likelihood (PPML) method to the gravity model using panel data on 49 exporting and 235 importing countries for 17 years from 2000 to 2016. The gravity model is estimated using both interval data and dynamic analyses. The results show that domestic subsidies have a modest but significant impact on dairy-product trade across the models. For example, a 1% increase in subsidies leads to a roughly 0.02% increase in trade for an average country. Memberships in trade agreements, market size factors, and government institutions also positively affect dairy-product trade. However, tariffs are insignificant in the main model specification. Results from the lag-policy analysis show that the impact of subsidies disappears after the second year of distribution, whereas for the lead-policy analysis, results suggest at least three years of anticipatory effects on domestic subsidies. 

Published: Kondaridze, M., & Luckstead, J. (2023). Determinants of dairy‐product trade: Do subsidies matter?. Journal of Agricultural Economics. 

Chapter 2: Navigating the Complexities of Dairy Trade: A Comprehensive Trade Policy and Frictions Analysis Using PPML and DR Methods

Abstract: Given the complex nature of international trade, we explore the average and distributional effects of trade policy and friction variables across different trade values using both recently developed Poisson Pseudo Maximum Likelihood (PPML) and distribution regression (DR) methods to estimate gravity models. We study the impacts of sanitary and phytosanitary (SPS) measures, technical barriers to trade (TBT), tariffs, different trade agreements, customs unions, and friction variables, such as distance, common languages, contiguity, and colonial history on bilateral trade flows of dairy products for 242 exporter and 243 importer countries between 1995 and 2019. The results from PPML gravity analyses suggest that SPS measures reported to WTO negatively affect dairy trade, while TBT boosts trade. We also observe significant trade agreements' effects on dairy trade. We further enhance our analysis by separating intra-distance from international distance to examine how the separate effects compare to the combined distance effect. The DR results, using the counterfactual effects analysis, show heterogeneous effects for the policy and friction variables. For example, TBT has a moderately positive and heterogeneous impact on dairy trade flows, which is becoming particularly pronounced for the upper quantiles of trade flows. We also find that distance shows a strong negative heterogeneous impact across the entire distribution of dairy trade flows.

Chapter 3: Production Subsidies and Agricultural Trade 

The main objective of this study is to analyze the impact of Producer Support Estimates (PSEs) on agricultural trade. To this end, I use counterfactual and machine learning analysis alongside the PPML models to examine the impact of these subsidies and other determinants on agricultural trade using panel data of 72 exporting and 256 importing countries for 20 years from 2000 to 2019. The analysis uses aggregated agricultural trade data to examine the impacts of aggregate and decomposed (commodity-specific and non-commodity-specific) domestic subsidies. I hypothesize a positive effect of PSEs on trade, as found in the first chapter. The results, however, offer a more nuanced perspective. While aggregate PSEs do not significantly affect agricultural trade, decomposing PSEs into commodity and non-commodity supports provides additional insights. The results indicate that the coefficients of commodity-specific supports are statistically insignificant. This may occur because the products that receive commodity-specific PSEs vary by country and are a subset of all agricultural commodities. This changing sub-set of commodities by country introduces substantial noise regarding the impact of these subsidies on aggregate trade. Therefore, this result suggests that the effects of commodity-specific PSEs need to be examined for individual commodities rather than aggregate agricultural trade (as is done in the first chapter). However, the coefficient of non-commodity-specific PSEs is positive and significant, confirming the hypothesis that subsidies increase exports. The next step is to study counterfactual effects, where subsidies are removed to evaluate the direct and indirect (i.e., third-party) impact on agricultural trade. Then, using machine learning approaches, I will allow the computer to help inform what factors determine trade, in contrast to making functional form assumptions and comparing counterfactual analyses using structural gravity versus machine learning. 

Empirical Evidence of Changing Food Demand and Consumer Preferences in Russia  

Abstract: We investigate food preference changes in Russia that may have resulted from political, economic, and other changes. Our empirical framework utilizes advances in consumer theory and exploits provincial-level panel data on food consumption and supply shifters to identify price and income effects. Our findings indicate that consumers underwent a structural preference change that began in 2007 and continued into 2014. To illustrate the magnitude of this change, we contrast economic effects for select food commodities across regions. The new insights will be useful in designing timely and effective food and trade policies, as well as informing strategy decisions of agribusiness industry players. 

Published: Hovhannisyan, V., Kondaridze, M., Bastian, C., & Shanoyan, A. (2020). Empirical evidence of changing food demand and consumer preferences in Russia. Journal of Agricultural and Applied Economics, 52(3), 480-501. 

"An Empirical Assessment of Effectiveness of the US Tobacco Control Policies: A Smoothed Instrumental Variables Quantile Regression Approach” with Vahe Heboyan and Vardges Hovhannisyan. Forthcoming in Empirical Economics

Abstract: A sound understanding of the potency of tobacco control policies is key to tobacco prevention. This study exploits a Smoothed Instrumental Variables Quantile Regression estimator to gauge the effectiveness of these policies while addressing major methodological and data limitations plaguing the previous literature. Specifically, smoke-free indoor air laws and tobacco control expenditures are examined in a single framework, which has the promise of accounting for potential synergies thereof. Further, endogeneity of price (a proxy for tax policy) and other tobacco control policies are addressed through a unique set of instruments while allowing for differential impacts across the conditional distribution of cigarette consumption. Finally, our use of the nationally representative individual-level price and consumption data is essential for the precise estimation of price elasticities and policy effects. Results indicate that ignoring price and policy endogeneity leads to inconsistent estimates. Further, tobacco expenditures are effective only for relatively more addicted smokers, while state-level smoke-free indoor laws lack efficacy. In contrast, tax policy appears to be most potent for less addicted individuals. Therefore, optimal policy responses should combine tobacco expenditures with sin taxes. 

• Kondaridze, M. and Luckstead, J. Production Subsidies and Agricultural Trade. Selected paper to be presented at the annual meeting of American Agricultural Economics Association, Washington, DC, July 23-July 25, 2023.

• Kondaridze, M. and Luckstead, J. Navigating the Complexities of Dairy Trade: A Comprehensive Trade Analysis Using Gravity Models. SES Graduate Student Seminar Series, WSU, Pullman, April 26, 2023.

• Kondaridze, M., Liu, X., and Luckstead, J. Quantile Effects of Non-Tariff Measures, Trade Agreements and Friction Variables on Bilateral Tarde Flows of Dairy Industry Via Distribution Regression. Selected paper to be presented at the annual meeting of American Agricultural Economics Association, Anaheim, CA, July 31-August 2, 2022.

• Kondaridze, M. Quantile Regression Estimation of NTMs and Trade Agreements for Dairy Industry. Selected poster to be presented at the SESGSA Poster Competition, WSU, Pullman, April 22, 2022.

• Kondaridze, M. and Luckstead, J. Determinants of Dairy Trade: Do Subsidies Matter? Selected poster to be presented at the GPSA Research Exposition, WSU, Pullman, March 31, 2022.

• Kondaridze, M. and Luckstead, J. Determinants of Dairy Trade: Do Subsidies Matter? SES Graduate Student Seminar Series, WSU, Pullman, December 8, 2021.

• Heboyan, V., Hovhannisyan, V., Bakhtavoryan R. and Kondaridze M. 2021. An Empirical Analysis of the Effectiveness of the US Tobacco Control Policies with Endogenous Polices and Prices. Selected paper to be presented at the annual meeting of American Agricultural Economics Association, Austin, TX, August 1-4, 2021.

• Hovhannisyan, V. and Kondaridze M. 2020. Urbanization and Subsistence Consumption: The Case of China. Selected paper to be presented at the annual meeting of Southern Agricultural Economics Association, Louisville, KY, February 1-4, 2020.

• Kondaridze, M. and Hovhannisyan, V. 2019. Consumer Food Preference Changes in Russia. Selected paper to be presented at the annual meeting of Southern Agricultural Economics Association, Birmingham, AL, February 2-5, 2019.

• Kondaridze, M. and Hovhannisyan, V. 2019. Welfare Consequences of Food Price Increase in Russia. Selected poster to be presented at the annual meeting of Southern Agricultural Economics Association, Birmingham, AL, February 2-5, 2019.

• Hovhannisyan, V. and Kondaridze, M. 2018. Changing Structure of Food Consumption in Russia. Selected poster to be presented at the annual meeting of Southern Agricultural Economics Association, Jacksonville, FL, February 2-6, 2018.