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Uncertainty, Markups and Price Dynamics: Implications for the Financial and Real Sectors.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Uncertainty, Markups and Price Dynamics: Implications for the Financial and Real Sectors./
作者:	Agrawal, Sneha.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:	218 p.
附註:	Source: Dissertations Abstracts International, Volume: 83-02, Section: B.
Contained By:	Dissertations Abstracts International83-02B.
標題:	Finance. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28318368
ISBN:	9798534675993

Uncertainty, Markups and Price Dynamics: Implications for the Financial and Real Sectors.
Agrawal, Sneha.

Uncertainty, Markups and Price Dynamics: Implications for the Financial and Real Sectors. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 218 p.

Source: Dissertations Abstracts International, Volume: 83-02, Section: B.

Thesis (Ph.D.)--New York University, 2021.

This item must not be sold to any third party vendors.

Economic decisions are often based on expectations about the future path of relevant economic variables that affect the trade-offs faced by the decision maker. Such expectations often deviate from the eventual realization of these economic variables, more so in light of economic and political uncertainty. As a result, decision makers either ex-ante modify their strategy to account for fluctuations in economic variables, or ex-post modify their optimal response to shocks or news. Moreover since economic entities are highly inter-twined, such dynamic and heterogeneous responses across economics agents propagate through the economy, and lead to important ramifications for the financial and real sector outcomes. This collection of essays seeks to analyze these issues by combining macroeconomic theory with careful empirical analyses of micro-data.In Chapter 1, I study the effect of uncertainty in the foreign value of the US dollar on the US banking sector and subsequently, the US real economy. I propose a novel 'Exchange Rate (ER) Uncertainty Channel' to show how increased volatility in the trade-weighted US dollar index affects US bank lending. 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. Both, the price and volume effect is stronger for US banks with greater exposure to the SLM. Thus, volatility in the US dollar is a 'global risk indicator' that significantly affects the US bank lending activity. This channel leads to a contraction of in the quarterly US-GDP growth rate by 1% over 3 quarters. This chapter sheds light on financial implications of pervasive and persistent ER uncertainty.In Chapter 2, my co-authors Abhishek Gaurav, Melinda Suveg and I 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 in a large panel data of firms from Sweden. We find that one standard deviation higher oil price volatility leads to an increase in firm markups by 0.35% annually for the firm with average intensity of oil usage. Our mechanism captures one-tenth of the within industry standard deviation in firm markups.In Chapter 3, I consider an unanticipated policy shock to the Indian economy and analyze how the economic agents respond to it. 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 chapter, I build a theoretical framework to characterize the implications of demonetisation on the stationary monetary equilibrium of the economy. The chapter closely explains the trade-off 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. This shows that political shocks/ news have important real implications for a country's monetary system.Finally in Chapter 4, I examine the network propagation of inflation and output dynamics in response to financial shocks for the US production economy. In this co-authored chapter with Simon Gilchrist, Egon Zakrajsec, we use a spatial dynamic factor model to estimate the strength of network effects in industry's response to demand shocks. Our empirical methodology allows us to decompose industry level responses into a direct effect and those resulting from a network propagation effect. Our results indicate that the US production sector exhibits 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.

ISBN: 9798534675993Subjects--Topical Terms:

542899
Finance.
Subjects--Index Terms:

Currency value

Uncertainty, Markups and Price Dynamics: Implications for the Financial and Real Sectors.
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500 $a Source: Dissertations Abstracts International, Volume: 83-02, Section: B.
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502 $a Thesis (Ph.D.)--New York University, 2021.
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520 $a Economic decisions are often based on expectations about the future path of relevant economic variables that affect the trade-offs faced by the decision maker. Such expectations often deviate from the eventual realization of these economic variables, more so in light of economic and political uncertainty. As a result, decision makers either ex-ante modify their strategy to account for fluctuations in economic variables, or ex-post modify their optimal response to shocks or news. Moreover since economic entities are highly inter-twined, such dynamic and heterogeneous responses across economics agents propagate through the economy, and lead to important ramifications for the financial and real sector outcomes. This collection of essays seeks to analyze these issues by combining macroeconomic theory with careful empirical analyses of micro-data.In Chapter 1, I study the effect of uncertainty in the foreign value of the US dollar on the US banking sector and subsequently, the US real economy. I propose a novel 'Exchange Rate (ER) Uncertainty Channel' to show how increased volatility in the trade-weighted US dollar index affects US bank lending. 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. Both, the price and volume effect is stronger for US banks with greater exposure to the SLM. Thus, volatility in the US dollar is a 'global risk indicator' that significantly affects the US bank lending activity. This channel leads to a contraction of in the quarterly US-GDP growth rate by 1% over 3 quarters. This chapter sheds light on financial implications of pervasive and persistent ER uncertainty.In Chapter 2, my co-authors Abhishek Gaurav, Melinda Suveg and I 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 in a large panel data of firms from Sweden. We find that one standard deviation higher oil price volatility leads to an increase in firm markups by 0.35% annually for the firm with average intensity of oil usage. Our mechanism captures one-tenth of the within industry standard deviation in firm markups.In Chapter 3, I consider an unanticipated policy shock to the Indian economy and analyze how the economic agents respond to it. 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 chapter, I build a theoretical framework to characterize the implications of demonetisation on the stationary monetary equilibrium of the economy. The chapter closely explains the trade-off 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. This shows that political shocks/ news have important real implications for a country's monetary system.Finally in Chapter 4, I examine the network propagation of inflation and output dynamics in response to financial shocks for the US production economy. In this co-authored chapter with Simon Gilchrist, Egon Zakrajsec, we use a spatial dynamic factor model to estimate the strength of network effects in industry's response to demand shocks. Our empirical methodology allows us to decompose industry level responses into a direct effect and those resulting from a network propagation effect. Our results indicate that the US production sector exhibits 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.
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650 4 $a Feedback. $3 677181
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653 $a Currency value
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653 $a Exchange rates
653 $a Markups
653 $a Input price pass-through
653 $a Policy shock
653 $a India
653 $a Demonetisation
653 $a Monetary equilibrium
653 $a Laundering
653 $a Inflation
653 $a Output dynamics
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