Agglomeration and firm-level productivity : a Bayesian spatial approach

This paper estimates the impact of industrial agglomeration on firm-level productivity in Chinese manufacturing sectors. To account for spatial autocorrelation across regions, we formulate a hierarchical spatial model at the firm level and develop a Bayesian estimation algorithm. A Bayesian instrumental-variables approach is used to address endogeneity bias of agglomeration. Robust to these potential biases, we find that agglomeration of the same industry (i.e. localization) has a productivity-boosting effect, but agglomeration of urban population (i.e. urbanization) has no such effects. Additionally, the localization effects increase with educational levels of employees and the share of intermediate inputs in gross output. These results may suggest that agglomeration externalities occur through knowledge spillovers and input sharing among firms producing similar manufactures.

Chapter 1 Economic Integration and Industry Location: Theories, Empirical Results, and Implications for CLMV

Trade affects the internal location of industry in two ways: it induces firms to specialize and it expands the set of markets that firms serve. If there are industry-specific external economies, firms in related industries will spatially agglomerate (Hanson 1996a). In the context of economic integration, diminished barriers to trade affect industry location particularly in less developed countries. As described below, regional agreements in North America and Europe have caused frontier regions to expand. These regions, which include border regions and port cities, have advantages over internal regions in terms of access to foreign markets. Since trade liberalization induces many firms in developing countries to participate in production networks and to specialize in labor-intensive activities such as assembling and processing of foreign-made components, their inputs as well as final products need to be carried across borders. Therefore, the best industry location, one that minimizes transport costs, is likely to shift to frontier regions. In East Asia, China has developed rapidly since it opened up to international trade. Simultaneously, a large amount of foreign direct investment (FDI) has been attracted and industry agglomerations have been formed in coastal regions, that is, frontier regions linked to the global market by sea, leaving many internal regions behind. Similarly, Cambodia, Laos, Myanmar, and Vietnam (CLMV) have joined AFTA and/or the WTO and liberalized international trade since the 1990s. Moreover, transport infrastructures such as the East-West Economic Corridor, the Southern Economic Corridor, and the North-South Economic Corridor have been built and narrowed economic distances in the Greater Mekong Subregion (GMS). As a result, frontier regions are likely to increase their location advantages and lure labor-intensive operations from neighboring countries. It is expected that, as has happened in North America and Europe, economic integration in East Asia will significantly affect internal geography in CLMV. In this study, I first review theories relevant to economic integration and industry location within a country. In particular, emphasis is placed on the new economic geography (NEG). Secondly, empirical results for North America and Europe are surveyed since they have preceded East Asia in regional integration and a substantial number of studies have been conducted on these regions. The final section summarizes and discusses implications for internal geography in CLMV.

Spatial spillover effects in determining China's regional CO2 emission growth : 2007-2010

This paper proposes an alternative input-output based spatial-structural decomposition analysis to elucidate the role of domestic-regional heterogeneity and interregional spillover effects in determining China's regional CO2 emission growth. Our empirical results based on the 2007 and 2010 Chinese interregional input-output tables show that the changes in most regions' final demand scale, final expenditure structure and export scale give positive spatial spillover effects on other regions' CO2 emission growth, the changes in most regions' consumption and export preference help the reduction of other regions' CO2 emissions, the changes in production technology, and investment preference may give positive or negative impacts on other region's CO2 emission growth through domestic supply chains. For some regions, the aggregate spillover effect from other regions may be larger than the intra-regional effect in determining regional emission growth. All these facts can significantly help better and deeper understanding on the driving forces of China's regional CO2 emission growth, thus can enrich the policy implication concerning a narrow definition of "carbon leakage" through domestic-interregional trade, and relevant political consensus about the responsibility sharing between developed and developing regions inside China.