Structural gravity with dummies only: Constrained ANOVA-type estimation of gravity models

American Economic Review

Nigai

Strecker

2019

Self Cite

Section: Globalization and Relative Labor Income Tax Burdens Acrosmentioning

confidence: 99%

The Taxing Deed of Globalization

American Economic Review

Nigai

Strecker

2019

Self Cite

“…Because proxy variables provide only approximate information on the economic process in the background, they are likely to contain noise (measurement error) which can be separated from the systematic variation when imposing a set of suitable assumptions. In general, Egger and Nigai (2014) provide evidence that parameterized trade cost functions appear to generally lead to sizable measurement errors with aggregate gravity models of bilateral international trade. In the introduction, we gave examples of earlier work that pointed to measurement problems with specific observable trade cost variables.…”

Section: A Random Coefficients Gravity Modelmentioning

confidence: 97%

“…This paper proposes an alternative approach, where at least observable (and, eventually, even unobservable) measures of trade costs may exert a direct effect on bilateral trade that is variable. It is well known that the measurement of many variables entering gravity-model specifications is imprecise (see Egger and Nigai 2014): Tariff rates may be improperly applied to the wrong product lines due to fraud (Fisman and Wei 2004) or may be badly recorded; distances between countries pertain to some arbitrary points in space (capital cities or economic centers) which may coincide with origins and destinations of exports and imports or not (see Hillberry and Hummels 2008); adjacency might matter differently for country pairs with longer or shorter borders (see Engel and Rogers 1996); common official language may mis-represent the importance of the actual overlap of (native or non-native) speakers between two countries (see Melitz and Toubal 2014); and domestic as opposed to foreign trade costs might be mis-measured (see Rousslang and To 1993). These issues of measurement error as well as specific responses per se might lead to heterogeneous direct effects of trade impediments on trade flows, which are typically assumed to be the same.…”

Section: Introductionmentioning

confidence: 99%

The determinants of trade costs: a random coefficient approach

Průša

2015

Empir Econ

This paper assesses whether the sensitivity of bilateral trade volumes to various trade cost factors is constant or varies across countries. It utilizes a random coefficient model and analyzes a cross-sectional sample of bilateral trade data for 96 countries in 2005. We expect the elasticity of trade to vary particularly with bilateral distance and bilateral tariffs due to measurement error about these factors. Indeed, the variability of coefficients is significant for these trade cost measures. The results indicate that the elasticity of trade with respect to tariffs in different countries varies relatively more than that with respect to distance. This is consistent with there being a host of sources of measurement error about bilateral tariffs (due to strategic or non-strategic mis-reporting; the potential inappropriateness of the weighting of disaggregated tariffs; etc.).

“…Hence, we can use the relationship

ln (\frac{λ_{n i, t}^{j}}{λ_{i i, t}^{j}}) = e_{i, t}^{j} + d_{i n, t}^{j} - e_{n, t}^{j},

where

e_{j, t}^{s}

and

e_{n, t}^{j}

are data on (log) unit‐cost measures. Hence, we can calculate trade costs in year t as:

τ_{i n, t}^{j} = exp (- \frac{1}{θ^{j}} d_{i n, t}^{j})

Then we can trace how trade costs changed across time and, using hat algebra for changes, define

{\overset{τ}{true}}_{i n, t}^{j} = τ_{i n, t}^{j} / τ_{i n, 1995}^{j} .

This approach is related to Egger and Nigai (). We plot the change in trade costs for agricultural goods, manufactures, and services across different percentiles of the data in Figure .…”

Section: Calibrationmentioning

confidence: 99%

Sources of heterogeneous gains from trade: Income differences and non‐homothetic preferences

Rev International Economics

Nigai

2018

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Global wage inequality is tightly linked to productivity-and remoteness-related income differences within and across countries. These sources of heterogeneous effects of globalization on wages are customary in quantitative work in trade which aims at examining the link between trade and inequality. However, the second source of heterogeneous effects of trade on income difference around the globe-non-homotheticity in preferences-has been largely ignored. We explore the relative importance of these two factors in explaining the link between globalization and global wage inequality. Abstract This paper considers the interrelationship between a hierarchy of consumption needs of agricultural goods, manufactures, and services as a central feature of the demand side of economies and the demand for skilled and unskilled workers, whose incomes differ. The relationship is established as skilled and unskilled labor are used in conjunction with capital goods in a nested constant-elasticity-of-substitution (CES) production function, which features capital-skill complementarity and a substitutive relationship between the bundle of capital and skills on the one hand and unskilled labor on the other hand. Incomes differ across countries both within and between types of workers. As trade costs change, relative and absolute incomes of worker types change and so does the workertype-specific pattern of consumption. A calibration and simulation exercise documents that a consideration of the supply-and-demand-side linkage in this hierarchy-ofneeds model matters quantitatively for the role of trade liberalization in the world economy.