Research Topics

Evidence From an Emerging Country, India

According to the theory of efficient markets, economic agents use all available information to form rational expectations. The rational expectations hypothesis asserts that information is scarce, the economic system generally does not waste information, and that expectations depend specifically on the structure of the entire system. Fiscal marksmanship—the accuracy of budgetary forecasting—can be one important piece of such information that rational agents must consider in forming expectations. Against the backdrop of fiscal rules, our paper explores the budgetary forecast errors of climate change–related public spending in India. The fiscal rules stipulate that fiscal deficit–to–GDP ratio should be maintained at 3 percent. However, in the post-COVID fiscal strategy, a medium-term fiscal consolidation path of 4.5 percent fiscal deficit–to­–GDP is envisioned by 2025–26. Within this fiscal consolidation framework, we analyzed the budget credibility of fiscal commitments for climate change in India. We analyzed the fiscal behavioral variables in terms of bias, variation, and randomness, and captured the systemic variations in budgetary forecast related to climate change for a period 2017–18 to 2020–21 across sectors. We identified the sectors where systematic components of forecasting errors are relatively higher than random components, where minimizing errors through altering the fiscal behavioral models is done by revising the assumptions and by applying better forecasting methods. A state-level decomposition of the public spending revealed that disaggregated fiscal space available for developmental spending constitutes around 60 percent of the total. However, identifying the specifically targeted public spending related to climate change across all states and analyzing its fiscal markmanship can further the subnational inferences.

Analyzing the Fiscal Forecasting Errors of 28 States in India

Budget credibility, or the ability of governments to accurately forecast macro-fiscal variables, is crucial for effective public finance management. Fiscal marksmanship analysis captures the extent of errors in the budgetary forecasting. The fiscal rules can determine fiscal marksmanship, as effective fiscal consolidation procedures affect the fiscal behavior of the states in conducting the budgetary forecasts. Against this backdrop, applying Theil’s technique, we analyze the fiscal forecasting errors for 28 states (except Telangana) in India for the period 2011–16. There is a heterogeneity in the magnitude of errors across subnational governments in India. The forecast errors in revenue receipts have been greater than revenue expenditure. Within revenue receipts, the errors are more significantly pronounced in the grants component. Within expenditure budgets, the errors in capital spending are found to be greater than revenue spending in all the states. Partitioning the sources of errors, we identified that the errors were more broadly random than due to systematic bias, except for a few crucial macro-fiscal variables where improving the forecasting techniques can provide better estimates.