Determinants of Trade Policy

In the last thirty years economists have paid increasing attention to determinants of trade policy. Well known in political economy literature (Grossman-Helpman-1994) ‘Protection for Sale’ (PFS) model aims to explain the structure of trade policy. This model emphasizes the influence of special interest groups (SIG) on government policy by means of ‘political contributions’ in a representative democracy. Organized interest groups represent industries and are offering contributions, which politicians value for their potential use in elections. The government chooses trade policy which maximizes a weighted sum of aggregate welfare and total contributions from SIGs. The relative preference of a government for aggregate welfare over contributions from a lobbyist is known in literature as the parameter ‘a’ or ‘welfare mindedness’ of the government. Despite the parameter ‘a’ is simplified in the government objective function, it contains an interesting information when it is observed in dynamics (for various years) or across different countries.

The empirical verification of PFS was conducted in several papers. (Goldberg-et-all-1999) and (Gawande-Bandyopadhyaya-2000) present first two empirical studies using the United States non-tariff industry-level data. Both papers found, as predicted by Grossman-Helpman model, that protection to organized sectors is negatively related to import penetration and import demand elasticity. (Goldberg-et-all-1999) paper states that the weight on the welfare in the government objective function is many times larger than the weight on contributions in the United States in 1983. The paper by (McCalman-2004) uses PFS model to analyze Australian trade liberalization process. The author concluded that the process of liberalization in the country was driven by increase in the parameter ‘a’- the government valuation of welfare. The paper by (Gawande-et-al-2009) presents the institutional determinants of differences in government trade policy formation (value of ‘a’) around the world based on PFS theoretical framework. The authors compared the values of the parameter ‘a’ across 54 countries and found the substantial variation in government behavior (‘a’) around the world. Thus, one of the notable finding of this paper suggests that the quality of the system of checks and balances embedded in the decision-making process correlate with higher welfare-mindedness of governments. (Mitra-et-al-2002) studied the case of Turkey in democracy vs. dictatorship periods. They found that the weight the government puts on the welfare (‘a’) is higher for democratic period than for dictatorship times in Turkey. The paper by (Evans-Sherlund-2011) used the PFS model to examine the relationship between anti-dumping decisions and the political contributions of Political Action Committees (PACs) in the US. (Gawande-et-al-2012) using modified version of PFS analyse the consequences of the lobbying competition between upstream and downstream producers. They find that the lobbying competition inclusion into the PFS model brings the value of ‘a’ in the government objective function down.

Thus, one can observe a variety of research questions in trade policy determination which were studied through the theoretical framework of PFS model.

During the Global Crisis (2008-2010) governments around the world resorted to protectionist commercial policies. The patterns and the structure of protectionist policies for 2008-2010 were analyzed in (Evenett-et-al-2011), (Evenett-2011), and (Aggarwal-Evenett-2012), and (Kee-et-al-2013). The studies show that the commercial policy choices in current crisis are somewhat different, both in the structure of measures used as well as in the volume of trade affected. (Aggarwal-Evenett-2012) especially emphasize the selective nature (among industries, firms etc.) of the government protection and return to industrial policies during current crisis. All those changes give rise to a question if the government mechanism of trade policy making in crisis is different from economic stability times and if so, how. I aim to approach this research question through analytical potential of the PFS model. The objective of this paper therefore is to test the predictions of the PFS model as well as to estimate the structural parameter ‘a’, the weight put by government on the welfare relative to contributions in the government objective function over several years. The main question to be answered is to what extent (quantitatively) trade policy making is different in crisis vs. economic stability times. What are the other factors which affected trade policy making during crisis?

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This study contributes to the existing literature on trade policy formation threefold. First, this paper uses PFS theoretical framework to study trade policy making during current global crisis. Second, the model was originally developed to describe trade policy making in western representative democracies. Therefore, it is interesting to see how general this model is and if this model has explanatory power for trade policy making in other forms of governance and political regimes such as ‘Putin-Medvedev tandem’.footnote{Even western democracies have different mechanisms of trade policy making depending on the government system, in the countries other than western democracies this variety is even wider.) Third, by conducting the residual regression anaylsis I offer other than in PFS variables which explain the structure of protection during crisis.

Russian Federation was chosen for three main reasons. First, it is important to keep in mind that ‘protection for sale’ presents a country which determines trade policy endogenously. Membership in the World Trade Organization (WTO) could violate the condition of endogeneity of trade policy making in the model. The WTO member countries are bound by various commitments which substantially limit their policy space and commercial policy responses in crisis. The WTO membership therefore implies exogenous character of trade policy anti-crisis responses. Russia, however, was the only G20 country which was not a member of the WTO during current crisis. Russia also suspended its WTO accession process for 2009-2010 to implement anti-crisis and industrial policies (see (Gerasimenko-2012)). Therefore, one can state that the trade policy making during crisis in Russia was determined endogenously as required by the model specification. Second, during current crisis many governments used ‘murky protectionism’ measures instead of import tariffs. However, the model does not necessarily hold if protectionist measures other than tariffs (and subsidies) are imposed. Therefore, Russia is a good empirical test for the PFS model as this country indeed actively used import tariffs as anti-crisis measures in years 2009-2010 (see, Global Trade Alert database for 2009-2010 years). Third, investigating trade policy in Russia from 2001 onwards is especially interesting as it gives an opportunity to look at the welfare mindedness of the same government (same political setting, so called ‘Putin-Medvedev tandem’) over time in various economic situations, i.e. stability period and crisis times. This paper uses import tariff data for 2001, 2005, 2009, and 2010.

The findings show that the government weight on welfare in the government’s objective function ‘a’ is estimated to be larger than the weight on contributions across all years of analysis. However, the welfare mindedness of the government ‘a’ in crisis (2009 and 2010) appears to be smaller relatively to preceding economic stability period in 2005. In other words, in crisis the government puts relatively more weight on contributions from lobbyists. This result is driven by industry or firms active lobbying to get government support in hard times of financial difficulty and government return to industrial policy. Indeed, the residual regression analysis supports this argument.

The structure of the paper is as follows. Section II reviews the Grossman-Helpman theoretical model. Section III presents the econometric specification and describes the data. Section IV provides the empirical results and robustness checks. Section V discusses further findings. Section VI concludes.

The Grossman – Helpman’s ‘Protection for Sale’ model is adopted in this paper for several reasons. First, this model gives clear predictions for the cross-sectoral structure of the tariff protection inside the country. Second, the model states that cross-sectional differences in protection can be explained by three variables: if the industry is organized or not, import penetration ratio, and import demand elasticity. This gives a background intuition for further empirical examination of the determinants of trade protection in various settings.