Causality Relationships between Total Exports with Agricultural and Manufacturing GDP in Tanzania

This paper, investigates causal relationships among agriculture, manufacturing and export in Tanzania by using time series data for the period between 1970 and 2005. The empirical results show in both sectors there is Granger causality where agriculture causes both exports and manufacturing. Exports also cause both agricultural GDP and manufacturing GDP and any two variables out of three jointly cause the third one. There is also some evidence that manufacturing does not cause export and agriculture. Regarding cointegration, pairwise agricultural GDP and export are cointegrated, export and manufacture are cointegrated. Agriculture and manufacture are cointegrated but they are lag sensitive. However, three variables, manufacturing, export and agriculture both together are cointegrated showing that they share long run relation and this has important economic implications.

Chapter 6 Economic integration and changes in industrial location in Vietnam

Vietnam has been praised for its achievements in economic growth and success in poverty reduction over the last two decades. The incidence of poverty reportedly fell from 58.1% in 1993 to 19.5% in 2004 (VASS [2006, 13]). The country is also considered to have only a moderate level of aggregate economic inequality by international comparisons. As of the early 2000s, Vietnam’s consumption-based Gini coefficient is found to be comparable to that of other countries with similar levels of per capita GDP. The Gini index did increase between 1993 and 2004, but rather slowly, from 0.34 to 0.37 (VASS [2006, 13]). Yet, as the country moves on with its market oriented reforms, the question of inequality has been highlighted in policy and academic discourses. In particular, it is pointed out that socio-economic inequalities between regions (or provinces) are significant and have been widening behind aggregate figures (NCSSH [2001], Mekong Economics [2005], VASS [2006]). Between 1993 and 2004, while real per capita expenditure increased in all regions, it grew fastest in those regions with the highest per capita expenditures and vice versa, resulting in greater regional disparities (VASS [2006, 37]). A major contributing factor to such regional inequalities is the uneven distribution of industry within the country. According to the Statistical Yearbook of Vietnam, of the country's gross industrial output in 2007, over 50% belongs to the South East region, close to 25% to the Red River Delta, and about 10% to the Mekong River Delta. All remaining regions share some 10% of the country's gross industrial output. At a quick glance, the South East increased its share of the total industrial gross output in the 1990s, while the Red River Delta started to gain ground in more recent years. How can the government deal with regional disparities is a valid question. In order to offer an answer, it is necessary in the first place to grasp the trend of disparities as well as its background. To that end, this paper is a preparatory endeavor. Regional disparities in industrial activities can essentially be seen as a result of the location decisions of enterprises. While the General Statistics Office (GSO) of Vietnam has conducted one enterprise census (followed by annual enterprise surveys) and two stages of establishment censuses since 2000, sectorally and geographically disaggregated data are not readily available. Therefore, for the moment, we will draw on earlier studies of industrial location and the determinants of enterprises’ location decisions in Vietnam. The remainder of this paper is structured as follows. The following two sections deal with the country context. Section 2 will outline some major developments in Vietnam’s international economic relations that may affect sub-national location of industry. According to the theory of spatial economics, economic integration is seen as a major driver of changes in industrial location, both between and within countries (Nishikimi [2008]). Section 3, on the other hand, will consider some possible factors affecting geographic distribution of industry in the domestic sphere. In Section 4, existing literature on industrial and firm location will be examined, and Section 5 will briefly summarize the findings and suggest some areas for future research.

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.