"All I'm armed with is research" ― Mike Wallace
Job Market Paper
Uncertainty in the foreign value of the US dollar affects the US banking sector and therefore, the US real economy. In this paper, I propose a novel ‘Exchange Rate (ER) Uncertainty Channel’ to show the effects of increased volatility in the trade-weighted US dollar index for the US banking sector. Higher volatility in the exchange rate, leads to retrenchment by foreign banks from the US syndicated loans market (SLM). This entails a loanable funds supply bottleneck for the US banks trying to finance their loans through syndicates. US banks respond with tighter credit standards in an attempt to re-allocate scarce funds. In response to a 1 standard deviation increase in ER volatility, US banks’ net interest margin increase by 10 bps annualized, whereas balance sheets contract by 2-3 pp annualized. This is consistent with banks exerting market power in the loan market while simultaneously shrinking their balance sheets. Both, the price and volume effect is stronger for US banks with greater exposure to the SLM as measured by their loans-to-interest-earning-assets ratio. Thus, volatility in the US dollar is a ‘global risk indicator’ that significantly affects the US banking lending activity.
Production Networks and Trade Dynamics (with Simon Gilchrist, New York University, and Egon Zakrajšek, Fed Board and BIS)
US industries are highly intertwined through complex demand and supply chains. We use a spatial dynamic factor model to assess the strength of network effects in each industry’s response to demand shocks. Our analysis relies on a rich panel data set for output, prices, wages and employment at a narrowly defined industry level. We integrate it with BEA input-output tables, trade shares, financial spreads and commodity indices to quantify and analyze the nature of industries and their concomitant strength of network spillovers.
Our empirical methodology allows us to decompose industry level responses into a direct effect and those resulting from network spillovers. Our results indicate that the US Production Sector exhibit strong network spillovers in response to a demand shock. This is particularly true for output, prices and wages where spillovers account for between 50-80% of the average industry response. In contrast, our estimates imply that the response of industry level employment is primarily due to the direct effects of aggregate fluctuations on industry activity. We also document that network spillovers are strongest in tradeable goods industries that are much farther down in the supply chain. As a result of these strong spillovers, the inflation response of tradeable goods industries to demand shocks is weaker compared to the more upstream non-tradeable industries. Effectively, tradeable goods industries exhibit greater price rigidity. Consistent with this finding, tradeable goods industries also exhibit larger fluctuations in output in response to aggregate demand shocks.
Cited by Gopinath et al (QJE 2020)
On 8th November 2016, Government of India announced the surprise ‘Demonetisation’ of ₹500 (US $7.70) and ₹1000 (US $15) bank notes replacing them with new notes. The government claimed that this action would curtail the shadow economy and crack down the use of illicit and counterfeit cash to fund illegal activity. The sudden nature of the announcement and the prolonged cash shortages in the weeks that followed - created significant disruption throughout the Indian economy. In this paper, I build a theoretical framework to explain some of the stylised facts of demonetisation in India and characterize it’s implications on the stationary monetary equilibrium of the economy. The paper closely explains the tradeoff faced by the agents with regards to holding black money and evading taxes on one hand and getting heavily penalised if caught by the auditors on the other. The model also explains how money laundering naturally emerges when the government compels agents to reveal their true taxable incomes via demonetisation.
Work In Progress
Input Price Uncertainty and Markups (with Abhishek Gaurav, Princeton University and Melinda Suveg, Uppsala University)
In this paper, we propose a new channel to explain higher markups and incomplete pass-through of input prices to markups. Standard models in the literature often do not consider second-moment changes in input prices, that is, the uncertainty in costs the producers face while deciding prices. This uncertainty, along with the fact that prices are sticky as the firms often choose prices knowing only their cost distribution and not the actual cost realization, might lead to much lower dividends than expected. As a result, firms have a precautionary motive to charge higher markups ex-ante and insure against high future cost uncertainty. We corroborate this with evidence on oil-price and real-exchange-rate volatility shocks in a large panel data of firms from Sweden. We find that higher cost uncertainty for firms with intensive use of oil or imports (respectively) leads to an increase in markups by 3%-7% annualized.