The impact of improved highways on Indian firms☆
Section snippets
Introduction and Motivation
This paper studies the effects of an ambitious program of highway improvements in India on firms in that country. It is motivated by – and contributes to – a large literature on the economic effects of investments in large-scale infrastructure, a key issue in development. Highways, the quintessential example of such infrastructure investments, are studied in papers such as Michaels, 2008, Chandra and Thompson, 2000, Fernald, 1998.
Such infrastructure investments are often posited as being
The Indian Highway System
India's road network, which carries 65 per cent of the country's freight (World Bank 2007), is dominated by its 66,000 kilometer-long network of 228 federally built and maintained National Highways. These connect major cities in the country to one another, and carry 40 per cent of the country's road traffic in spite of comprising only 2 per cent of its aggregate road length of 3.3 million kilometers. The prominent role played by the National Highway system has motivated policymakers to pay
Identification Strategy: The Golden Quadrilateral Project as a Natural Experiment
As discussed in Section 1, the key issue that makes it difficult to estimate the causal effect of infrastructure such as highways is that of non-random placement, which means that places that receive more or better infrastructure are likely to be systematically different from areas that do not. However, as Chandra and Thompson (2000) have pointed out, the nature of many large highway network projects allows them to be used as an exogenous shock to areas that they pass through. The argument
Data Sources and Contents
The outcome data used in this paper are from two rounds of the World Bank Enterprise Surveys for India, carried out in the years 2002 and 2005. The firms surveyed were a random sample of firms in India's formal sector stratified by sector of activity, firm size and geographical location so as to generate a sample of firms “representative of the whole non-agricultural private economy” of the country (World Bank 2009).
A subset of firms in 37 Indian cities were surveyed in both years, giving us a
Input Inventories: Leaner Inventory Management
Table 2a presents the means and standard deviations of the inventory stock variable for three categories of firms: those in cities not on the Golden Quadrilateral, those in “intermediate cities” (i.e. not in one of the nodal cities or their suburbs), and those in the nodal cities/their suburbs. For each category, the table has the mean number of days of inventory held by firms in 2002 (the pre-period) and 2005 (the post-period). As argued in Section 3, the cleanest comparison is between “non-GQ
Conclusions
Firms in cities that lay along one of the four national highways connecting the four largest cities in India that the Indian government upgraded as part of its Golden Quadrilateral report holding about 10.5 days’ worth of production less of input inventories in 2005, when much of the project had been implemented, than in 2002, when work had just begun, while firms which lay in cities off the Golden Quadrilateral highways report no such change. Similar results are obtained when distance from the
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This work was initiated and a first draft written while at the World Bank. Revisions were carried out while at The Economist, London. I would like to thank Simeon Djankov for his early support, and Esther Duflo for her encouragement.