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Sujit Kapadia

Macro Prud Policy&Financial Stability

Division

Market-Based Finance

Current Position

Head of Division

Fields of interest

Financial Economics,Macroeconomics and Monetary Economics

Email

Sujit.Kapadia@ecb.europa.eu

29 November 2023
THE ECB BLOG
Details
JEL Code
G32 : Financial Economics→Corporate Finance and Governance→Financing Policy, Financial Risk and Risk Management, Capital and Ownership Structure, Value of Firms, Goodwill
G38 : Financial Economics→Corporate Finance and Governance→Government Policy and Regulation
G11 : Financial Economics→General Financial Markets→Portfolio Choice, Investment Decisions
Q56 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Environment and Development, Environment and Trade, Sustainability, Environmental Accounts and Accounting, Environmental Equity, Population Growth
Q58 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Government Policy
Q01 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→General→Sustainable Development
10 May 2023
WORKING PAPER SERIES - No. 2813
Details
Abstract
Using evidence from the EU emissions trading system, we collect verified emissions of close to 4000 highly polluting and mostly non-listed firms responsible for 26% of EU’s emissions. Over the period 2013 - 2019, we find a non-linear relationship between leverage and emissions. A firm with higher leverage has lower emissions in subsequent years. However, when leverage exceeds 50%, a further increase is associated with higher emissions. Our difference-in-differences approach sheds light on the existence of a group of firms that are too indebted to successfully accomplish the low-carbon transition, even when they face a steep increase in the cost of their emissions.
JEL Code
C58 : Mathematical and Quantitative Methods→Econometric Modeling→Financial Econometrics
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
G32 : Financial Economics→Corporate Finance and Governance→Financing Policy, Financial Risk and Risk Management, Capital and Ownership Structure, Value of Firms, Goodwill
Q51 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Valuation of Environmental Effects
Q56 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Environment and Development, Environment and Trade, Sustainability, Environmental Accounts and Accounting, Environmental Equity, Population Growth
Q58 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Government Policy
14 November 2022
WORKING PAPER SERIES - No. 2747
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Abstract
Funds with an environmental, social and corporate governance (ESG) mandate have been growing rapidly in recent years and received inflows also during periods of market turmoil, such as March 2020, in contrast to their non-ESG peers. This paper investigates whether investors in ESG funds react differently to past negative performance, making these funds less sensitive to short-term changes in returns. In the absence of an ESG-label, we define an ESG- or Environmentally-focused fund if its name contains relevant words. The results show that ESG/E equity and corporate bond funds exhibit a weaker flow-performance relationship compared to traditional funds in 2016-2020. This finding may reflect the longer-term investment horizon of ESG investors and their expectation of better risk-adjusted performance from ESG funds in the future. We also explore how the results vary across institutional and retail investors and how they depend on the liquidity of funds’ assets and wider market conditions. A weaker flow-performance relationship allows funds to provide a stable source of financing to the green transition and may reduce risks for financial stability, particularly during turmoil episodes.
JEL Code
G11 : Financial Economics→General Financial Markets→Portfolio Choice, Investment Decisions
G23 : Financial Economics→Financial Institutions and Services→Non-bank Financial Institutions, Financial Instruments, Institutional Investors
Q56 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Environment and Development, Environment and Trade, Sustainability, Environmental Accounts and Accounting, Environmental Equity, Population Growth
C58 : Mathematical and Quantitative Methods→Econometric Modeling→Financial Econometrics
21 December 2021
WORKING PAPER SERIES - No. 2631
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Abstract
This paper explores how the need to transition to a low-carbon economy influences firm credit risk. It develops a novel dataset which augments data on firms’ green-house gas emissions over time with information on climate disclosure practices and forward-looking emission reduction targets, thereby providing a rich picture of firms’ climate-related transition risk alongside their strategies to manage such risks. It then assesses how such climate-related metrics influence two key measures of firms’ credit risk: credit ratings and the market-implied distance-to-default. High emissions tend to be associated with higher credit risk. But disclosing emissions and setting a forward-looking target to cut emissions are both associated with lower credit risk, with the effect of climate commitments tending to be stronger for more ambitious targets. After the Paris agreement, firms most exposed to climate transition risk also saw their ratings deteriorate whereas other comparable firms did not, with the effect larger for European than US firms, probably reflecting differential expectations around climate policy. These results have policy implications for corporate disclosures and strategies around climate change and the treatment of the climate-related transition risk faced by the financial sector.
JEL Code
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
G11 : Financial Economics→General Financial Markets→Portfolio Choice, Investment Decisions
G32 : Financial Economics→Corporate Finance and Governance→Financing Policy, Financial Risk and Risk Management, Capital and Ownership Structure, Value of Firms, Goodwill
Q51 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Valuation of Environmental Effects
Q56 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Environment and Development, Environment and Trade, Sustainability, Environmental Accounts and Accounting, Environmental Equity, Population Growth
C58 : Mathematical and Quantitative Methods→Econometric Modeling→Financial Econometrics
22 November 2021
WORKING PAPER SERIES - No. 2614
Details
Abstract
We develop early warning models for financial crisis prediction by applying machine learning techniques to macrofinancial data for 17 countries over 1870–2016. Most nonlin-ear machine learning models outperform logistic regression in out-of-sample predictions and forecasting. We identify economic drivers of our machine learning models using a novel framework based on Shapley values, uncovering nonlinear relationships between the predic-tors and crisis risk. Throughout, the most important predictors are credit growth and the slope of the yield curve, both domestically and globally. A flat or inverted yield curve is of most concern when nominal interest rates are low and credit growth is high.
JEL Code
C40 : Mathematical and Quantitative Methods→Econometric and Statistical Methods: Special Topics→General
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
F30 : International Economics→International Finance→General
G01 : Financial Economics→General→Financial Crises
17 July 2019
OCCASIONAL PAPER SERIES - No. 227
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Abstract
This occasional paper describes how the financial stability and macroprudential policy functions are organised at the ECB. Financial stability has been a key policy function of the ECB since its inception. Macroprudential policy tasks were later conferred on the ECB by the Single Supervisory Mechanism (SSM) Regulation. The paper describes the ECB’s macroprudential governance framework in the new institutional set-up. After reviewing the concept and origins of systemic risk, it reflects on the emergence of macroprudential policy in the aftermath of the financial crisis, its objectives and instruments, as well as specific aspects of this policy area in a monetary union such as the euro area. The ECB’s responsibilities required new tools to be developed to measure systemic risk at financial institution, country and system-wide level. The paper discusses selected analytical tools supporting financial stability surveillance and assessment work, as well as macroprudential policy analysis at the ECB. The tools are grouped into three broad areas: (i) methods to gauge the state of financial instability or prospects of near-term systemic stress, (ii) measures to capture the build-up of systemic risk focused on country-level financial cycle measurement and early warning methods, and (iii) the ECB stress testing framework for macroprudential purposes.
JEL Code
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
F36 : International Economics→International Finance→Financial Aspects of Economic Integration
G20 : Financial Economics→Financial Institutions and Services→General
G28 : Financial Economics→Financial Institutions and Services→Government Policy and Regulation
K23 : Law and Economics→Regulation and Business Law→Regulated Industries and Administrative Law
6 May 2019
WORKING PAPER SERIES - No. 2278
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Abstract
This paper explores monetary-macroprudential policy interactions in a simple, calibrated New Keynesian model incorporating the possibility of a credit boom precipitating a financial crisis and a loss function reflecting financial stability considerations. Deploying the countercyclical capital buffer (CCyB) improves outcomes significantly relative to when interest rates are the only instrument. The instruments are typically substitutes, with monetary policy loosening when the CCyB tightens. We also examine when the instruments are complements and assess how different shocks, the effective lower bound for monetary policy, market-based finance and a risk-taking channel of monetary policy affect our results.
JEL Code
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
G01 : Financial Economics→General→Financial Crises
G28 : Financial Economics→Financial Institutions and Services→Government Policy and Regulation
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