This study examines the effects of the robotic subsidy policy in China’s manufacturing sector. The demand-side subsidy policy aims at encouraging manufacturing firms to invest in robotics by lowering the cost of purchase. Our difference-in-difference analysis reveals distributional impacts of municipality-level robot subsidies on manufacturing firms of different scales. Although the subsidy brings a 14.2% increase in the application of robot patents, the facilitated access to robotics has not transformed into new firm entries. Strikingly, new firm entry decreases by 23.5% after the policy implementation. On the other hand, robot subsidies have increased the revenue, total asset, and employment of larger manufacturing firms by 9.8%, 6.9%, and 6.7%, respectively. To interpret the mechanism, we develop a simplified framework incorporating financial frictions into a task-based model. The model reveals that idiosyncratic borrowing costs lead to an inefficient equilibrium by generally depressing automation adoption and creating automation dispersion across firms. Such ex-ante distortion results in a uniform subsidy disproportionately benefiting firms with better capital access, thus creating a trade-off in terms of efficiency: while the subsidy can enhance overall automation, it simultaneously exacerbates automation dispersion. To quantify the efficiency implications, we embed this simplified model into a dynamic heterogeneous-agent framework, calibrated to the 2010 productivity distribution, financial frictions, and robot density in the industrial sector in China. Our dynamic model reveals that a 20% robot subsidy narrows the gap between mean and optimal automation level by 22% percentage points, while raises automation dispersion by 49%. This results in a 1.23% increase in aggregate output at the cost of a 2.40% decline in TFP. This dynamic model proposes a novel mechanism that automation exacerbates capital misallocation by enlarging asset accumulation dispersion between workers and entrepreneurs. Controlling for this dynamic feedback could enhance the subsidy-induced output gain by an additional 26%

This paper argues that ffnancial lease, a dominant representation of shadow banking in China, plays a special role in improving the capital allocation efficiency. In a two-sector general equilibrium model with heterogeneous firm, information asymmetry and financial frictions, this paper shows that existence of finance lease market increases aggregate TFP by allowing low productivity SOE firms to lend out and allowing high productivity POE firms to leverage up. Due to the repossession advantage, financial leasing is a “good“ form of shadow banking that does not necessarily cause financial systemic risks.

Debt covenants are pervasive in debt contracts. To prevent the dilution of existing debt, most creditors set covenants of a maximum debt-to-earnings ratio for borrowing firms. In this paper, we embed debt covenants into a workhorse real business cycle model with defaultable debt to study its macroeconomic implications. In our model, creditors penalize firms when debt covenants are violated. We show such a mechanism that covenants significantly reduce debt dilution and default over the business cycles. Furthermore, reduced debt dilution due to debt covenants also mitigates the debt overhang problem and thus boosts capital accumulation. Compared to counterfactual economies without covenants, the baseline economy with debt covenants experiences endogenous stabilization of macroeconomic shocks and higher levels of capital, output, and consumption.

We develop a heterogeneous-agent model with local spatial markets to study the relationships among bank expansion, growth, and inequality. In the model, households choose their occupations, consumption, and holdings of loans and portfolio assets that vary by liquidity. Banks choose the locations of new branches, which affect the financial frictions facing households across regions. We calibrate the model using a geographic information system to evaluate the rapid bank expansion in Thailand between 1986-1996. The model quantifies the sources of growth and inequality over time and a cross space and the potential role of digital banking in substantially reducing regional heterogeneity.

This paper investigates the consequences of liquidation and reorganization on the allocation and subsequent utilization of assets in bankruptcy. Using the random assignment of judges to bankruptcy cases as a natural experiment that forces some firms into liquidation, we find that the long-run utilization of assets of liquidated firms is lower relative to assets of reorganized firms. These effects are concentrated in thin markets with few potential users, and in areas with low access to finance. The results highlight the importance of local search frictions and financial frictions in affecting the allocation of assets in bankruptcy.