following Contingent Liability Shocks

Subnational Government S in South aS ia 153

population, income, and the gap between the state’s income and that of the state with the highest income. These factors, and the weights assigned to them, vary among Finance Commissions. Our estimates suggest that central government support through grants is not affected by the shock. By contrast, tax devolution received from the central government increases by 10 percent in the year after a contingent liability shock.

Why does tax devolution respond but grants do not? This remains somewhat a puzzle. One possible explanation is that grants are fixed in nominal terms by the Finance Commission and are often earmarked and committed to specific projects. Therefore, they provide a limited leeway for responses. By contrast, the central government allegedly enjoys flexibility in the timing of the payout of tax devolution. This flexibility provides a mechanism to counter fiscal shocks at the subnational level. Taken together, the evidence is consistent with an interpretation that states enjoy rather soft budget constraints that partially buffer the impact of realizations of contingent liabilities.

What Are the Economic Costs of Adjustments to Contingent Liability Shocks?

Do debt shocks at the subnational level affect local investments and dampen local economic development? Such negative spillovers could occur for various reasons. For one, debt shocks can reduce public capital expenditure— as we have shown. This reduction, in turn, decreases public capital formation as well as private investment that relies on the execution of public investment (such as connective infrastructure) and that is typically “crowded in” by public investment. In addition, contingent liability shocks can dampen local investments indirectly—for instance, by raising the tax burden, and thus discouraging private capital formation, or by reducing the viability of investment projects, firm creditworthiness, and local lending by banks. For this reason, this section investigates the costs of subnational contingent liability shocks for the local economy. It does so by reestimating the previous difference-in-difference specification using gross fixed capital formation (GFCF) (in logs) in a given state and year as the outcome variable.

Figure 4.14 reports the results by plotting the estimated treatment effect estimated for five years before and after the occurrence of contingent liability shock. GFCF in the state

falls significantly in the year of a contingent liability shock, continues to decline in the year after, and remains significantly below

the trend for three years after the event. Then, it gradually returns to the trend. Reassuringly, the figure does not a identify significantly diverging trends between affected and unaffected states before the shock, suggesting that the observed divergence in trends is indeed driven by the contingent liability shock.

To quantify the impacts highlighted in figure 4.14, the coefficient estimates in table 4C.3, column 1, in annex 4C, confirm that GFCF falls significantly below its trend following a contingent liability shock. The capital formation experiences a maximum

FIGURE 4.14 Decreases in Indian Subnational Governments’ Gross Fixed Capital Formation following Contingent Liability Shocks

0.4

Percentage di erence between treatment and control 0.2

0

−0.2

−0.4

−0.6

−5 −4 −3 −2 −1 0 1 2 3 4 5 Years relative to distress event

Source: Blum and Yoong 2020. Note: The figure plots the coefficient estimates βs of the following regression:

5 it +it s j t it0Log GFCF CL .s∑ α β γ µ ε( ) = + + + +

=− s 5

Each coefficient measures the relative value of gross fixed capital formation (GFCF, in logs) s years before and after a contingent liability shock, compared to states with no such shock. The x-axis plots the time relative to the shock. The y-axis plots the values for the corresponding βs.