Search results

This chapter examines the role of immigrant networks on trade, particulalry through the demand effect. First, we examine the effect of immigration on trade when the immigrants consume more of the good that is abundant in their home country than the natives in a standard Heckscher–Ohlin model and find that the effect of immigration on trade is a priori indeterminate. Our econometric gravity model consisting of 63 major trading and immigrant-sending country for the United States over 1991–2000. We find that the immigrants income, mostly through demand effect has a significant negative effect on U.S. imports. However, if we include the effect of the immigrant income interacted with the size of the immigrant network, measured by the immigrant stock, we find that higher immigrants income lowers the immigrant network effect for both U.S. exports and imports. This we find in addition to the immigrants stock elasticity of 0.27% for U.S. exports and 0.48% for U.S. imports. Capturing the immigrant assimilation with the level of immigrant income and the size of the immigrant enclave this chapter finds that the immigrant network effect on trade flows is weakened by the increasing level of immigrant assimilation.

This paper revisits the derivation and properties of the Allen-Uzawa and Morishima elasticities. Using a Swiss dataset, this paper empirically estimates various elasticities both in a dual and primal framework using a production theory open economy model and tests for linear homogenous technology. In addition to reporting elasticity at the mean, the standard practice in the literature, this paper also calculates nonparametric distribution of various elasticities. The paper aims to discuss these issues.

To assess the effect of price change on input, the paper estimates a translog cost function and to assess the effect of quantity change on price, the paper estimates the translog distance function using the data on Swiss economy. The paper estimates Allen-Uzawa and Morishima elasticity both under homogenous and non-homogenous technology using the Swiss dataset of one aggregate gross output and four inputs (resident labor, non-resident labor, imports, and capital) over 1950-1986. Elasticities are reported and compared at the mean as well as explored by looking at the range and nonparametric distribution.

This paper shows that constant returns to scale are easily rejected in this dataset and that the elasticities, both qualitatively and quantitatively, are very different under homogenous and non-homogenous technology. These elasticities can switch from complements to substitutes or vice versa when one moves away from the mean of the sample. The equality of the nonparametric elasticity distributions under homogenous vs non-homogenous technology is rejected in all cases except one.

This paper gives a clear derivation and interpretation of different elasticities as well as demonstrates using a dataset how to systematically go about empirically estimating these elasticities in a dual and primal framework. It shows that linear homogenous technology can be easily rejected and the elasticities, both quantitatively and qualitatively, are very different under homogenous and non-homogenous technology. This paper is also very valuable because it shows that the standard practice of reporting elasticity at the mean might not be adequate and there is a possibility that these elasticities can switch from complements to substitutes or vice versa when one moves away from the mean of the sample.

The purpose of this paper is to examine the effect of cyclical and structural factors on the decline of maquiladora employment. In addition to the US industrial production, the cyclical factors examined are relative Mexican US wages, the Mexican exchange rate relative to the US, and US foreign direct investment (FDI). The paper also explores the effect of competition from China, a structural effect, on the decline of maquiladora employment.

A vector error correction (VEC) model of maquila employment for the period 1980‐2002 is estimated and controlled for US industrial production, FDI flows, relative wage rates of Mexico and USA. To empirically investigate the structural differences of lower costs in Mexico vs China a seemingly unrelated regression (SUR) is estimated across three sectors: apparel and textile, electronic, and transportation.

From the VEC maquila employment model it is found that, in addition to the strong effect of US industrial production on the maquila employment, there exist significant short‐ and long‐run effects of Mexico US exchange rate and Mexican wages relative to USA on maquila employment. The sectoral (SUR) model shows that competition from China has a bigger adverse effect on relatively labor‐intensive good and commodities which are cheaper to transport (such as textiles) over more bulky transportation goods. The transportation sector has a location advantage, though is more sensitive to the cyclical fluctuations in the US industrial production.

Future research should investigate the role of USA and world FDI exclusively into Mexico and maquiladora sector.

Well designed controls, output choice, and location advantage are important for the growth and viability of small scale manufacturing industries.

The VEC model for maquila employment and the SUR framework across main maquila sectors is the first to account for wages, exchange rate, and FDI in addition to the US industrial production in understanding the decline in maquiladora employment.

The purpose of this chapter is to assess the importance of individual social capital characteristics in determining wages, both directly through their valuation by employers and indirectly through their impact on individual occupational choice. We find that a person’s level of sociability and care for others works through both channels to explain wage differences between social and nonsocial occupations. Additionally, expected wages in each occupation type are found to be at least as important as a person’s level of social capital in choosing a social occupation. We make use of restricted 2000 Decennial Census and 2000 Social Capital Community Benchmark Survey.