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Does autonomy matter in state owned enterprises? Evidence from performance contracts in India
No full textThe empirical effect of enterprise autonomy on the performance of state-owned enterprises is surprisingly scant despite autonomy being a preferred reform instrument in many countries, and often chosen over privatization. Using longitudinal data on performance contracts for state-owned enterprises in India, this paper empirically examines whether granting increased autonomy to state-owned enterprises through such contracts positively impacts enterprise profitability. Further, using the unique reform experience of India as a natural experiment, whereby enterprise autonomy has
been simultaneously pursued with partial privatization for a sub-set of enterprises, a unique contribution of the study lies in investigating whether ownership divestiture through partial privatization has any effect once enterprises are imparted managerial autonomy, or whether ownership per se matters. Classifying state owned enterprises into three types, namely those that have been granted autonomy, those with autonomy and partially divested ownership, and those with neither, the study finds robust evidence of a positive impact of managerial autonomy on enterprise profitability. Additionally, once autonomy is controlled for, the study finds at best a weak effect of partial privatization. These results raise doubt on earlier findings of a robust positive effect of partial
privatization in India in studies that did not explicitly control for enterprise autonomy thereby raising the possibility that the positive privatization effect that showed up was in actuality, an autonomy effect
Anticipated money, unanticipated money and real effects: A test of the Barro proposition in the Indian context
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Sector GDP concentration bias in the Macro-Money demand specification: New evidence for India
No full textMoney serves as an intermediate target variable for transmitting monetary policy actions in macroeconomic management. In this connection, no other macro-behavioral function is subjected to more modelling modifications and regression rigors than the macro-money demand function. Monetary policy planning crucially depends on the parameters of the money demand function. An emerging market economy undergoes structural change in the sector GDP composition when compared to that of a structurally (invariant) mature advanced economy. This obviously introduces a bias in the estimation of the income elasticity of money demand parameter if the structural change were not modelled into the money demand function. The present study tries to incorporate this structural change into the money demand function as an additional variable besides the aggregate GDP and interest rate as the conventional scale and opportunity cost parameters variables respectively. The simplified algebra permits us to proxy the sector GDP concentration variable by the numbers equivalent Herfindahl index(H) For the opportunity cost variable,1-3 year deposit rate and the call money rate are
alternatively used. Maximum Likelihood estimates of the have thrown up a statistically highly significant positive coefficient of the H variable besides equally highly significant scale and opportunity cost variables with their expected positive and negative coefficients respectively. This empirical evidence suggests that without this variable, the conventional specification of the money demand function contains a serious policy-centric specification error. Also, the implication of the result is that as the sector GDP concentration increases, the demand for real money balances increases less proportionately, indicating presence of economies of scale
A Systematic approach to identify systemically important firms
No full textThis paper uses the average of the percentile ranking of three measures of systemic risk { Granger Causality, Marginal Expected Shortfall,and Conditional Value at Risk { to calculate a single systemic risk index (SRI) for a firm. The SRI is used to identify systemically important firms (SIFs) among the 50 largest firms in a quarter. This has the advantage of identifying SIFs on a regular basis using readily available data. The paper uses this approach to identify SIFs by SRI each quarter from 2000 to 2012, and finds that the cumulative risk of the SIFs tracks the changes in systemic risk in India during the
2008 crisis. The paper also finds merit in monitoring non-financial firms by their SRI, particularly when bank loan portfolios have concentrated exposures in these firms
Child Work and Schooling in rural north India : What do time use data say about tradeoffs and drivers of human capital investment?
No full textThis study examines time use data for 1244 children in the age-group 6-12 years in 274 villages in eight states in rural north India to understand the tradeoffs between time spent in school, time spent at work, time spent on home study and leisure. Using a Seemingly Unrelated Regression (SURE) Model, we find that only a few variables influence allocation of time to different activities across the board. Overall, there seems to be no tradeoff between time spent at school and at work, whereas leisure time and home study appear to be compromised for the sake of work
Diversification, merger and their effect on firm performance: A study of the Indian corporate sector
No full textGrowth drivers: ICT and Inclusive innovations
No full textThe paper explores the contribution of innovations to Indian growth. Inclusive innovations aid catch-up and close productivity gaps. An analytical framework helps to characterize policies that contribute to such innovations. Recent telecommunication and mobile banking policies are assessed against these. While policy can directly encourage it, if innovation depends on market size above a threshold, policies
that expand size can be more effective in inducing innovation. While policy successfully expanded mobile use, increasing revenue has recently taken precedence over expanding the market. Poor provision of the relevant infrastructure continues to exclude sections of the population and limit spillovers. Regulatory measures that limited market size were partly responsible for India's lack of success in mobile banking, compared to Pakistan