In this paper we contribute to the literature on the measurement of international trade flows. Specifically, we combine changes in the volume and quality in matched trade changes to present a simple new index together with a geometric framework that can be used to visualise changes in quality and volume simultaneously. We illustrate the usefulness of our simple extension with data for trade between Malaysia and China between 1994 and 2004.
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Theoretically, Falvey (1981), Falvey and Kierzkowski (1985) and Flam and Helpman (1987) show that, even without increasing returns to scale, large numbers of firms will produce varieties of different quality. More recently, an empirical literature has developed to quantify the importance of product variety (see e.g. Hummels and Klenow 2005; Schott 2004; Broda and Weinstein 2006).
The precise meaning of the SAH remains subject to differing interpretation although an excellent clarification of the three key components of the SAH, which are trade as an exogenous variable, adjustment costs and IIT, can be found in Brulhart et al. (2006). There is insufficient space to go into detail although simply put, “trade induced” adjustment refers to changes in the domestic market that can be traced back to changes in prices or volume relative to the rest of the world. See also Davidson and Matusz (2001, 2004) and Bacchetta and Jansen (2003) for recent assessments of trade-induced adjustment costs.
Eicher (1996) discusses the relationship between human capital and technological change with higher technological innovation (improvements in quality) being associated with more skilled labour (skill-biased labour demand) and an increase in the relative wage of skilled to unskilled labour.
Azhar et al. (2008) follow the three stage approach and investigate the robustness and sensitivity of the existing approaches to measuring VIIT and HIIT (Greenaway et al. 1999; Fontagné and Freudenberg 1997; Azhar and Elliott 2006) using data on the nature of trade flows between China and its East Asian neighbours.
The premise for using UVs is that goods of a higher quality should demand a higher price (Stiglitz 1987). Thus, price can be considered an imperfect indicator of quality. Greenaway et al. (1994) and Aiginger (1997) provide discussion. Such comparisons however ignore the fact that that prices may also differ due to comparative advantage (Hallak and Schott 2005). Schott (2004) demonstrates that exporter skill and capital abundance are positively related to the within-product variation in export unit values. Unit values as a surrogate for price indices has also been criticised for being liable to measurement bias due to poor data quality and the mix of heterogenous items within product groupings (Silver 2007).
Rodrik (2006) and Azhar et al. (2008) use UVs to compare the quality of Chinese exports with those from other East Asian countries while Schott (2006) compares Chinese export UVs within different product categories to the prices received by other US trading partners. See Hummels and Klenow (2005) for a general study looking at the relationship between the variety and quality of a nation’s exports and Funke and Ralf (2001) for an East Asian study of export variety and export performance.
The choice of the 85% cut-off point is arbitrary but the choice is no different to the 15% or 25% cut-off used in previous measures. See Azhar and Elliott (2006) for a longer debate on this issue.
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A.K.M. Azhar is grateful to the Malaysian Ministry of Science, Technology and Innovation for funding grant number 54322. The usual disclaimer applies.
In the appendix we briefly describe a possible weighting procedure. For example, if one believed that volume based adjustment costs are two or three times more severe that quality induced adjustment then appropriate weights could be applied. However, the chosen weights would be arbitrarily. One solution would be to weight the VQ index by estimating the following equation;
Where, Δempit is labour turnover in country i at the t, S it and MQ it are S and MQ indices respectively, X it is a vector of control variables, and ε it is the error term. The estimates of α and β would then tell us the effect of changes in volume and changes in quality based IIT on employment, which we can then use as the weights when calculating the VQ index. Dependent variables that have been considered include labour turnover (Brülhart 2000), occupational or sectoral labour movement (Greenaway et al. 2002; Brülhart et al. 2006) and sectoral movement (Elliott and Lindley 2006; Cabral and Silva 2006).
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Azhar, A.K.M., Elliott, R.J.R. A Measure of Trade Induced Adjustment in Volume and Quality Space. Open Econ Rev 22, 955–968 (2011). https://doi.org/10.1007/s11079-010-9186-9