The Great Trade Collapse: An Evaluation of Competing Stories

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The Great Trade Collapse: An Evaluation of Competing Stories

One sentence summary: Retail inventories have contributed the most to the great trade collapse and the corresponding recovery, followed by protectionist policies, intermediate-input trade, and trade finance.

The corresponding paper by Hakan Yilmazkuday has been accepted for publication at Macroeconomic Dynamics.

The corresponding working paper is available here.

 
Abstract

The reduction in international trade has been more than the reduction in economic activity during the 2008 financial crisis, against the one-to-one relationship between them implied by standard trade models. This so-called the great trade collapse (GTC) has been investigated extensively in the literature resulting in alternative competing stories as potential explanations. By introducing and estimating a DSGE model using eighteen quarterly series from the U.S., including those that represent the competing stories, this paper evaluates the contribution of each story to GTC. The results show that retail inventories have contributed the most to the collapse and the corresponding recovery, followed by protectionist policies, intermediate-input trade, and trade finance. Productivity and demand shocks have played negligible roles.

Non-technical Summary
The reduction in international trade has been more than the reduction in economic activity during the 2008 financial crisis. This observation has been accepted as extraordinary, because its magnitude has been far larger than in previous downturns; accordingly, it has been called as the Great Trade Collapse (GTC, henceforth).

Since the relation between trade and economic activity is one to one in standard trade models (mostly implied by constant elasticity of substitution preferences in gravity-type studies), this collapse in trade has attracted attention in the recent literature, and its causes have been investigated extensively not only because the decline in trade flows relative to overall economic activity is surprisingly high but also because it has important implications for optimal policy response. Accordingly, alternative explanations have been achieved, including the dynamics of inventories, intermediate-input trade, compositional differences between traded goods and GDP, trade finance/credit, declining aggregate demand, or higher trade costs due to protectionist policies. Since most of these papers have competing stories, they have sometimes found conflicting results with each other as well. However, what if there were multiple stories contributing to GTC at the same time? If yes, what was the contribution of each story? In other words, are these stories complements of or substitutes to each other? Based on the literature introduced so far, answering these questions requires a structural estimation of a dynamic trade model with ingredients such as intermediate-input trade, inventories, protectionist policies, trade finance, and financial interactions between countries.

Accordingly, this paper introduces a dynamic stochastic general equilibrium (DSGE) trade model to create a bridge between the literatures of international trade and macroeconomics through investigating trade patterns in a dynamic framework that borrows the stories explaining GTC from the literature introduced above. The model considers individuals, manufacturers and retailers, where the latter two hold inventories of finished goods. There is a monetary authority who decides for the policy rate, although the interest rate faced by individuals (due to intertemporal choices) and manufacturers/retailers (due to financial needs, including trade finance) is subject to the country-specific risk premium. To consider compositional effects, the model distinguishes between traded versus nontraded goods, home versus foreign goods, and durable versus nondurable goods.

The model is estimated by state-of-the-art Bayesian techniques using eighteen series of quarterly data from the U.S., including durable and nondurable imports, durable and nondurable production, services versus overall consumption, prices, inventories, duties, risk premium, and wages. The estimated model is further used to decompose durable and nondurable imports into their components, representing the competing stories of intermediate-input trade, retail inventories, protectionist policies, trade finance, retail productivity shocks, and consumer demand shocks. When overall U.S. imports are considered, the results show that retail inventories have contributed the most to GTC and the corresponding recovery, followed by protectionist policies, intermediate-input trade, and trade finance. The compositional effects within imports are significant: while retail inventories are mostly responsible for the changes in durable imports, intermediate-input trade is responsible for the changes in nondurable imports. In all cases, productivity and demand shocks have played negligible roles.

 

The corresponding paper by Hakan Yilmazkuday has been accepted for publication at Macroeconomic Dynamics.

The corresponding working paper is available here.

 

 

 

Gravity Channels in Trade

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Gravity Channels in Trade

One sentence summary: Gravity variables in international trade capture the effects of indirect (rather than direct) trade costs.

The corresponding academic paper by Yulin Hou, Yun Wang and Hakan Yilmazkuday has been accepted for publication at Journal of International Trade & Economic Development.

 

Working paper version is available here.


Abstract
Gravity variables such as distance, adjacency, colony, free trade agreements or language are used to capture the effects of trade costs in empirical studies. By using actual data on trade costs, this paper decomposes the overall effects of such variables on trade into those through three gravity channels: duties/tariffs (DC), transportation-costs (TC), and dyadic-preferences (PC). As opposed to the existing literature where gravity variables act like supply shifters (through DC and TC), this paper empirically shows that they act like demand shifters (through PC). Regarding policy, it is implied that welfare-improving globalization cannot be achieved only through reductions in direct costs such as duties/tariffs or transportation costs; it is rather the globalization itself that should be promoted in order to shift the preferences of destination countries toward international products and thus reduce indirect trade costs. The results are further connected to several existing discussions in the literature, such as welfare gains from trade and the distance puzzle.


Non-technical Summary
Gravity models have been employed to connect trade flows to masses of economic activity at source and destination countries together with dyadic/gravity variables such as distance, common language, border, colonial relationship, and free trade agreements. Independent of the microfoundations, the estimated gravity equation model can be expressed in a log-linear format where log trade enters as the dependent variable, while source and destination effects together with dyadic variables representing trade costs enter as independent variables.

Within this picture, dyadic/gravity variables have been shown to be the main focus of estimations, since they are directly linked to any policy investigation due to their representation of trade costs. Although economic models imply that dyadic/gravity variables capture such trade costs, mostly corresponding to the difference between source and destination prices, it is understood in the background that these dyadic/gravity variables may also be capturing preferences in the destination country.

In this paper, we differentiate between the effects of dyadic/gravity variables on preferences and trade costs by using actual data on trade costs of U.S. imports. In particular, trade costs are defined as the difference between source and destination prices, including both duties/tariffs and transportation costs while excluding local distribution costs. Having data on trade costs (together with the standard data of trade and unit prices) directly allows us calculating the effects of dyadic/gravity variables on the measured data we have.

In order to show the contribution of this paper in a clear way, we consider two types of preferences. The first type of preferences is random (as we call it the case of "random preferences"), which is mostly the case in the literature as we show in details. When these "random preferences" are considered, the effects of gravity variables are only through direct trade costs that are embedded in destination prices. Hence, gravity variables act like supply shifters in this case (as is standard in the literature), because they are parts of the marginal costs of delivering the product to the destination country.

The second type of preferences we consider is the one that depends on dyadic/gravity variables (as we call it the case of "dyadic preferences"). These preferences constitute the main contribution of this paper. When these "dyadic preferences" are considered, the effects of gravity variables are not only through direct trade costs that are embedded in destination prices but also through preferences of individuals at the destination country (that represent indirect trade costs). Hence, in this case, gravity variables not only act like supply shifters (as is standard in the literature) but also act like demand shifters (that are new in this paper). It is implied that "dyadic preferences" in this paper represent a more general case than "random preferences" in the literature.

The model introduced in this paper is estimated separately for each type of preferences. These estimations are essential to figure out the channels through which gravity variables affect international trade. In particular, we would like to know whether gravity variables act like supply shifters or demand shifters. The estimation results show that when "random preferences" are considered, about one third of the effects of gravity variables on international trade are due to the channel of duties/tariffs, while the rest is due to the channel of transportation costs; hence, gravity variables act like supply shifters by construction in this case. In order to show the contribution of this paper, when the more general case of "dyadic preferences" is considered, virtually all the effects of dyadic/gravity variables on U.S. imports are due to preferences, while the effects through duties/tariffs and transportation costs are very small. It is implied that when the overall effects of gravity variables on international trade are considered, they are mostly through dyadic preferences, and thus gravity variables act like demand shifters (rather than supply shifters as implied by the literature).

These results have important policy implications for having a welfare-improving globalization. In particular, policy tools acting like supply shifters such as duties/tariffs or investment on transportation technologies are simply implied as not having enough impact on; it is rather the globalization itself that should be promoted in order to shift the demand preferences of destination countries toward international products.

As a supplementary exercise, we also investigate the contribution of each gravity variable to each gravity channel. In the case of both random and dyadic preferences, distance is shown to be the dominant gravity variable for the channels of duties/tariffs and transportation costs. However, for the channel of dyadic preferences that captures virtually all the effects of gravity variables on U.S. imports, the tables turn as having a common border contributes about 45.12%, followed by distance about 32.23%, colony about 13.98%, free trade agreement (FTA) about 6.91%, and language about 1.76%.

As an additional supplementary exercise, we finally investigate the contribution of each given gravity variable through alternative gravity channels. In the case of random variables, the effects of distance, common border, colonial relationship, and common language are shown to be mostly through transportation costs, whereas the effects of FTAs are through duties/tariffs. In the case of dyadic preferences though, all gravity variables are shown to be effective through the channel of dyadic-preferences rather than duties/tariffs or transportation costs.

The results are further connected to several existing discussions in the literature, such as the distance puzzle or welfare gains from trade. In particular, we show that the distance puzzle can easily be solved by decomposing the effects of distance into those due to transportation costs, duties/tariffs and dyadic preferences. Moreover, welfare gains from trade are estimated to be relatively higher in the case of dyadic preferences, which is ignored in the existing literature.

 

 

The corresponding academic paper by Yulin Hou, Yun Wang and Hakan Yilmazkuday has been accepted for publication at Journal of International Trade & Economic Development.

 

Working paper version is available here.

Daily Exchange Rate Pass-through into Micro Prices

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Daily Exchange Rate Pass-through into Micro Prices

One sentence summary: Daily exchange rate pass-through (ERPT) into micro prices of Turkish agricultural products is about 5 percent, while less perishable products have higher ERPT of about 10 percent.

The corresponding paper by Renzo Alvarez, Amin Shoja, Syed Uddin and Hakan Yilmazkuday been published at Applied Economics Letters.

The working paper version is available here.


Abstract
This paper estimates the exchange rate pass-through (ERPT) by using good-level daily data on wholesale prices of imported agricultural products, where the identification is achieved by using daily data on the domestic inflation rate. The results of standard empirical analyses are in line with existing studies that employ lower frequencies of data by showing evidence for incomplete daily ERPT of about 5 percent. The key innovation is achieved when nonlinearities in ERPT are considered, where ERPT is doubled to about 10 percent when daily nominal exchange rate changes are above 0.55 percent, daily frequencies of price change are above 3.12 percent, and storage life of a product is above 10 weeks. Important policy implications follow.


Non-technical Summary
Exchange rate pass-through (ERPT) is the standard measure used to represent the relationship between nominal exchange rates (NER) and prices of internationally traded goods. Since central banks that have the objective of price stability can intervene the exchange rate market to have full or partial control over the value of their currency, policy makers need to know how prices would react to changes in NER. Such knowledge is also essential for individual welfare through income and substitution effects, especially for small-open economies.

Within this picture, we investigate ERPT at the product-level by introducing a new data set that has two main advantages over the ones employed in the existing literature. First, we have daily wholesale price data on 52 imported agricultural products that cover the period between January 2005 and August 2015 in Turkey; to our knowledge, this is one of the few rich data sets based on daily observations of micro prices. Second, we have the corresponding daily prices for domestically produced agricultural products as well, so that the pure effects of NER changes on prices can be identified with respect to other macroeconomic developments.

Having a daily (rather than a lower frequency) investigation is essential for understanding the dynamics in the import prices of agricultural goods, because the effects of NER changes can only be investigated in a high frequency setup due to the perishable nature of these products (e.g., having a storage life of one week for raspberry). We combine the daily import price data of agricultural products with the corresponding data on NER, frequency of price change (measured over the sample period, thanks to the micro-price nature of the data) and storage life (a concept corresponding to the opposite of perishability/depreciation) to estimate ERPT, where we consider potential nonlinearities through estimated thresholds in these variables.

The results provide evidence for incomplete daily ERPT of about 5 percent, on average across agricultural products. The key innovation is achieved when nonlinearities in ERPT are considered, where ERPT is doubled to about 10 percent when daily nominal exchange rate changes are above 0.55 percent, daily frequencies of price change are above 3.12 percent, and storage life of a product is above 10 weeks. 

These results can be perceived as positive for Turkish policy makers, since low and incomplete pass-through as in this paper (i) ensures that NER shocks do not destabilize the price level and thus facilitates the prediction of future Turkish inflation, (ii) helps the stabilization of CPI inflation (targeting) rather than that of non-traded goods prices, and (iii) provides higher degrees of freedom to the monetary authority to conduct an independent policy, without having a trade-off between real stability and inflation stability, because high nominal exchange rate volatility is allowed to stabilize the real economy in face of external shocks.

Gains from Domestic versus International Trade: Evidence from the U.S.

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Gains from Domestic versus International Trade: Evidence from the U.S.

One sentence summary: Domestic trade contributes about 94 percent to overall welfare gains from trade, whereas the contribution of international trade is only about 6 percent.

The corresponding paper by Hakan Yilmazkuday has been accepted for publication at The Journal of International Trade & Economic Development.

The working paper version is available here.

Abstract

Using varieties of a rich model that considers sectoral heterogeneity and input-output linkages, this paper shows that the overall welfare gains of a region within a country can be decomposed into domestic versus international welfare gains from trade. Empirical results based on sector- and state-level data from the U.S. suggest that about 94 percent of the overall welfare gains of a state is due to domestic trade with other states. The ocean states gain from international trade about two times the Great Lake states and about three times the landlocked states.

Non-technical Summary

Domestic trade of a typical state in the U.S. is about five times its international trade, where about three quarters of this domestic trade is achieved with other states. It is implied that a typical state is about 20 percent open to international trade, while it is about 60 percent open to domestic trade. Since welfare gains from trade are known to be directly connected to such openness measures for a vast variety of models, the greater part of the welfare gains are implied to be through domestic trade. Nevertheless, since domestic trade data are not available for the majority of the countries, the existing literature has mostly focused on international welfare gains from trade that represent only a small portion of overall welfare gains.

Within this picture, this paper introduces a rich model considering sectoral heterogeneity as well as input-output linkages, where the unit of investigation is set as regions representing U.S. states. As standard in the literature, the corresponding welfare gains from trade are shown to be a function of expenditure shares and model parameters, where changes in expenditure shares are used to capture the changes in welfare in case of a hypothetical change in trade costs. The corresponding literature has focused on the hypothetical case of an autarky in the context of international trade. This paper follows this literature by having the same definition of international autarky while calculating the international welfare gains from trade.

The main contribution of this paper is achieved by considering an additional/alternative hypothetical case of autarky, namely domestic autarky, which is useful to calculate the domestic welfare gains from trade. In particular, domestic autarky is defined as the case in which a region still imports products internationally, but the domestic trade with other regions of the same country is shut down in this hypothetical case. It is shown that the overall percentage welfare gains from trade is the summation of domestic and international welfare gains from trade.

Based on the significant difference between international and domestic openness measures of states in the U.S., the corresponding welfare analysis shows that about 94 percent of the overall percentage welfare gains of a state are due to domestic trade with other states, on average across alternative model specifications, with a range between 85 percent and 99 percent across states.

The results have also shown that the ocean states gain from international trade about two times the Great Lake states and about three times the landlocked states. Since this result is partly due to the international openness of these states and partly due to considering a multi-sector framework, it is implied that the ocean states gain more from international trade not only because they overall trade more internationally but also certain sectors in these states are dependent more on international trade (e.g., "Chemical products" or "Transportation equipment"). This result is also reflected as the landlocked states gaining more from domestic trade compared to the coastal states, consistent with earlier studies in the literature suggesting that landlocked regions trade less than coastal regions due to facing higher trade costs.

Spatial Dispersion of Retail Margins: Evidence from Turkish Agricultural Prices

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Spatial Dispersion of Retail Margins: Evidence from Turkish Agricultural Prices

One sentence summary: The farmer share of Turkish grocery prices is only about 16 percent, corresponding to about 84 percent of a distribution share (77 percent of retail margins and 7 percent of transportation costs).

The corresponding paper by Hakan Yilmazkuday has been published at Agricultural Economics.

The working paper version is available here.

Abstract

The farmer share of retail prices is shown to be about 16 percent, corresponding to about 84 percent of a distribution share, on average across agricultural products and regions within Turkey. The share of transportation costs in retail prices is only about 7 percent, while the share of retail margins is about 77 percent of retail prices. The dispersion of retail prices across regions is shown to be mostly due to local wages and variable markups, while the contribution of traded-input prices is relatively small. Accordingly, the high dispersion of farmer prices across locations is not reflected in the dispersion of retail prices due to the high contribution of retail margins. These retail margins are also shown to account for about one third of the consumer welfare dispersion across regions and more than half of the consumer welfare dispersion across products.

Non-technical Summary

The portion of agricultural retail prices received by farmers, the so-called farmer share, is about 15 percent across countries. Accordingly, the distribution share consisting of transportation costs and retail margins constitute the bigger portion of retail prices. The decomposition of this distribution share into its components is important to understand the welfare and policy implications for both consumers and farmers. For example, if the distribution share is high due to transportation costs, the optimal policy to improve welfare would be to reduce them through investments on infrastructure or subsidies on transportation-related costs, while if the distribution share is high due to retail margins, they can be subject to effective price regulations that can increase consumer welfare due to lower prices and increase farmer welfare due to higher sales. Since retail margins increase with the market share, the effects of retail margins (and thus the corresponding price regulation) may even be higher in regions with higher market power. Accordingly, it is essential to have a decomposition of the distribution share both an average and across regions to achieve optimal policies.

This paper achieves such decomposition by using retail- and farm-level micro price data on agricultural products across Turkish regions. In order to have an empirical motivation and implications for welfare, a simple model is introduced, where the economic environment consists of regions inhabited by individuals who consume local retail goods and retailers who purchase traded-inputs from producers subject to transportation costs. Since we empirically focus on individual products of green groceries, producers correspond to farmers who produce homogenous goods. Accordingly, each retailer searches for the minimum price across farmers at the product level, subject to transportation costs. Once transportation costs and source farms are identified through estimations based on price data obtained from both farmers and retailers, traded-input prices are determined for retailers. By further introducing a structure on local retail costs through the model, the retail prices are decomposed into farmer prices and distribution costs (consisting of transportation costs and retail margins).

The empirical results show that the farm share is about 16 percent of retail prices on average across agricultural goods and regions, corresponding to about 84 percent of a distribution share. The share of transportation costs in retail prices is only about 7 percent, while retail margins (defined as the ratio of retail to traded-input prices including transportation costs) are about 4.47, implying that about 77 percent of retail prices are accounted for by the retail sector. This result corresponds to slightly higher transportation costs within Turkey compared to similar costs in the U.S. of about 4 percent for food products. This may be surprising, because the U.S. is a much more spatially dispersed economy (due its land size) and thus one may expect lower transportation costs within Turkey. Nevertheless, since transportation costs between farmers and retailer highly depend on fuel prices, the difference in transportation costs of Turkey and the U.S. can easily be attributed to ratio of fuel prices in Turkey to those in the U.S. which has an average of about 2.6 between 1994 and 2011 according to World Development Indicators. 

When a comparison is achieved across regions, the dispersion of retail prices is mostly due to local wages and variable markups (95 percent), while the contribution of traded-input prices is relatively small (5 percent). When we further investigate the dispersion of traded-input prices across locations, the contribution of transportation costs dominate by 95 percent, while that of source prices is only 5 percent. It is implied that the high dispersion of farmer prices across locations is not reflected in the dispersion of retail prices due to factors such as local input costs, variable markups, and transportation costs. It is also shown that retail margins are dispersed across regions at the product level. The implications of the model suggest that the dispersion of retail margins (across regions) is explained 52 percent by traded-input prices, and 48 percent by local wages and variable markups. Since the dispersion of traded-input prices is mostly due to transportation costs, it is implied that final consumers face different retail margins across locations due to all of transportation costs, local wages and variable markups.

Finally, using the implications of the model for consumer welfare, on average across individual products, about 30 percent of the consumer welfare dispersion is explained by retail margins across Turkish locations, while another 70 percent is explained by differences in either real economic sizes of regions or traded-input prices. On the other hand, within the same location, retail margins contribute by about 60 percent to the consumer welfare dispersion across products. Hence, the retail margin (that can be mostly explained by local wages and variable markups) is one of the key variables in understanding the dispersion of consumer welfare across regions.

The corresponding working paper by Hakan Yilmazkuday is available here.