Technical efficiency and productivity analysis in Indonesian provincial economies

Abstract

This article estimates inefficiency and Total Factor Productivity (TFP) across Indonesian provinces from 1993 to 2000. Indonesia is a large emerging market economy, but provinces within the country (due to the island structure of the country) are more distinct from one another compared to other countries. We use a stochastic frontier methodology to estimate inefficiency and TFP. We find that TFP fell by an average rate of 7.5% across provinces due to the decrease in technical efficiency. In fact, the majority of output growth within Indonesia is explained by the accumulation of inputs. In this sense, economic growth within Indonesia does not appear to be sustainable without reversing these trends.

Acknowledgements

We would like to thank two referees for their suggestions in improving the article, Budy Resosudarmo for providing much of the data, and Tim Coelli for making the software available to us.

Notes

¹ Fisher (1922), Törnqvist (1936) and Malmquist (1953) provide early examples. Solow (1957) decomposed US Gross Domestic Product (GDP) growth into two components, one driven by increases in capital and labour and the other driven by growth in TFP.

² To contrast, consider the New York City vicinity where great interaction occurs among New York, New Jersey and Connecticut, and so considering these states as distinct economic units becomes more tenuous.

³ This time period contains the financial crisis that hit the region in 1997 and a cause for concern is to what extent this crisis impacts our results. However, Nieh (2002) finds little evidence that pre- and post-crisis productivities differ in their dynamics or in variance decompositions.

⁴ One can also compute a Malmquist productivity index with a stochastic frontier model, but only if one assumes constant returns to scale. We do not opt to make such a restrictive assumption here.

⁵ Battese and Coelli (1992, 1995) examine efficiency levels of paddy farmers in India. Piesse and Thirtle (2000) estimate efficiency gains in Hungarian agricultural and manufacturing firms during the transition away from communism. Other references are provided in Coelli et al. (1998) and Kumbhakar and Lovell (2000). Hill and Kalirajan (1993) consider technical efficiency in the Indonesian garment industry that is more applicable to this study.

⁶ Indonesia currently has 31 provinces. However, some of these provinces were recently created. For the purposes of this study, we consider the provinces as they were defined from 1993 to 2000. East Timor is not considered since it obtained independence in 1999.

⁷ The assumption is that provinces with larger capital stocks also have larger capital accumulations. This could arise because more accumulation is necessary to replace depreciated capital or because of inertia as provinces that have accumulated capital rapidly along some transition continue to do so (although perhaps not as quickly). However, if poorer, low capital provinces ‘converge’ to rich provinces in that capital accumulation is greater for these poorer provinces then stocks and accumulations of capital are negatively associated. The coefficients on the capital terms in Equation 5 would then be negative. These low capital provinces would also appear to be less efficient than in reality since high capital accumulations would coincide with lower output. However, the coefficients on the capital terms from Equation 5 and Table 2 suggest to us that this is not the case.

⁸ However, Kim and Lee (2006), using a stochastic frontier model, find that economic growth for many East Asian countries stems from rising TFP and not merely from input accumulation.