Financing Choice and Local Economic Growth: Evidence from Brazil
Iftekhar Hasan, Thiago Christiano Silva, Benjamin Miranda Tabak
Journal of Economic Growth,
Nr. 3,
2021
Abstract
We study how financing non-traditional local activities, conceived here as a proxy for activity diversification, is associated with economic growth. We use municipality-level data from Brazil, a country with large geographical, social, and economic disparities observed across its more than 5500 municipalities. We find that finance to non-traditional local activities associates with higher municipal economic growth, suggesting a positive externality between the non-traditional and traditional sectors. Using large natural disasters in Brazil as sources of unexpected negative events, we find that this association between financing non-traditional local activities and economic growth becomes negative in times of distress. We find that traditional local sectors are more affected than non-traditional sectors following a natural disaster. Precisely because of the non-traditional sector’s dependence on the traditional sector, our results suggest that municipalities should restrengthen their traditional activities during adverse conditions.
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Conditional Macroeconomic Forecasts: Disagreement, Revisions and Forecast Errors
Alexander Glas, Katja Heinisch
IWH Discussion Papers,
Nr. 7,
2021
Abstract
Using data from the European Central Bank‘s Survey of Professional Forecasters, we analyse the role of ex-ante conditioning variables for macroeconomic forecasts. In particular, we test to which extent the heterogeneity, updating and ex-post performance of predictions for inflation, real GDP growth and the unemployment rate are related to assumptions about future oil prices, exchange rates, interest rates and wage growth. Our findings indicate that inflation forecasts are closely associated with oil price expectations, whereas expected interest rates are used primarily to predict output growth and unemployment. Expectations about exchange rates and wage growth also matter for macroeconomic forecasts, albeit less so than oil prices and interest rates. We show that survey participants can considerably improve forecast accuracy for macroeconomic outcomes by reducing prediction errors for external conditions. Our results contribute to a better understanding of the expectation formation process of experts.
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Disentangling Covid-19, Economic Mobility, and Containment Policy Shocks
Annika Camehl, Malte Rieth
IWH Discussion Papers,
Nr. 2,
2021
Abstract
We study the dynamic impact of Covid-19, economic mobility, and containment policy shocks. We use Bayesian panel structural vector autoregressions with daily data for 44 countries, identified through sign and zero restrictions. Incidence and mobility shocks raise cases and deaths significantly for two months. Restrictive policy shocks lower mobility immediately, cases after one week, and deaths after three weeks. Non-pharmaceutical interventions explain half of the variation in mobility, cases, and deaths worldwide. These flattened the pandemic curve, while deepening the global mobility recession. The policy tradeoff is 1 p.p. less mobility per day for 9% fewer deaths after two months.
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(Since when) are East and West German Business Cycles Synchronised?
Stefan Gießler, Katja Heinisch, Oliver Holtemöller
Jahrbücher für Nationalökonomie und Statistik,
Nr. 1,
2021
Abstract
We analyze whether, and since when, East and West German business cycles are synchronised. We investigate real GDP, unemployment rates and survey data as business cycle indicators and we employ several empirical methods. Overall, we find that the regional business cycles have synchronised over time. GDP-based indicators and survey data show a higher degree of synchronisation than the indicators based on unemployment rates. However, synchronisation among East and West German business cycles seems to have become weaker again recently.
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Financial Technologies and the Effectiveness of Monetary Policy Transmission
Iftekhar Hasan, Boreum Kwak, Xiang Li
Abstract
This study investigates whether and how financial technologies (FinTech) influence the effectiveness of monetary policy transmission. We use an interacted panel vector autoregression model to explore how the effects of monetary policy shocks change with regional-level FinTech adoption. Results indicate that FinTech adoption generally mitigates the transmission of monetary policy to real GDP, consumer prices, bank loans, and housing prices, with the most significant impact observed in the weakened transmission to bank loan growth. The relaxed financial constraints, regulatory arbitrage, and intensified competition are the possible mechanisms underlying the mitigated transmission.
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Energy Markets and Global Economic Conditions
Christiane Baumeister, Dimitris Korobilis, Thomas K. Lee
Abstract
This paper evaluates alternative indicators of global economic activity and other market fundamentals in terms of their usefulness for forecasting real oil prices and global petroleum consumption. We find that world industrial production is one of the most useful indicators that has been proposed in the literature. However, by combining measures from a number of different sources we can do even better. Our analysis results in a new index of global economic conditions and new measures for assessing future tightness of energy demand and expected oil price pressures.
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The Effects of Fiscal Policy in an Estimated DSGE Model – The Case of the German Stimulus Packages During the Great Recession
Andrej Drygalla, Oliver Holtemöller, Konstantin Kiesel
Macroeconomic Dynamics,
Nr. 6,
2020
Abstract
In this paper, we analyze the effects of the stimulus packages adopted by the German government during the Great Recession. We employ a standard medium-scale dynamic stochastic general equilibrium (DSGE) model extended by non-optimizing households and a detailed fiscal sector. In particular, the dynamics of spending and revenue variables are modeled as feedback rules with respect to the cyclical components of output, hours worked and private investment. Based on the estimated rules, fiscal shocks are identified. According to the results, fiscal policy, in particular public consumption, investment, and transfers prevented a sharper and prolonged decline of German output at the beginning of the Great Recession, suggesting a timely response of fiscal policy. The overall effects, however, are small when compared to other domestic and international shocks that contributed to the economic downturn. Our overall findings are not sensitive to considering fiscal foresight.
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The Evolution of Monetary Policy in Latin American Economies: Responsiveness to Inflation under Different Degrees of Credibility
Stefan Gießler
IWH Discussion Papers,
Nr. 9,
2020
Abstract
This paper investigates the forward-lookingness of monetary policy related to stabilising inflation over time under different degrees of central bank credibility in the four largest Latin American economies, which experienced a different transition path to the full-fledged inflation targeting regime. The analysis is based on an interest rate-based hybrid monetary policy rule with time-varying coefficients, which captures possible shifts from a backward-looking to a forward-looking monetary policy rule related to inflation stabilisation. The main results show that monetary policy is fully forward-looking and exclusively reacts to expected inflation under nearly perfect central bank credibility. Under a partially credible central bank, monetary policy is both backward-looking and forward-looking in terms of stabilising inflation. Moreover, monetary authorities put increasingly more priority on stabilising expected inflation relative to actual inflation if central bank credibility tends to improve over time.
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Why are some Chinese Firms Failing in the US Capital Markets? A Machine Learning Approach
Gonul Colak, Mengchuan Fu, Iftekhar Hasan
Pacific-Basin Finance Journal,
June
2020
Abstract
We study the market performance of Chinese companies listed in the U.S. stock exchanges using machine learning methods. Predicting the market performance of U.S. listed Chinese firms is a challenging task due to the scarcity of data and the large set of unknown predictors involved in the process. We examine the market performance from three different angles: the underpricing (or short-term market phenomena), the post-issuance stock underperformance (or long-term market phenomena), and the regulatory delistings (IPO failure risk). Using machine learning techniques that can better handle various data problems, we improve on the predictive power of traditional estimations, such as OLS and logit. Our predictive model highlights some novel findings: failed Chinese companies have chosen unreliable U.S. intermediaries when going public, and they tend to suffer from more severe owners-related agency problems.
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How Forecast Accuracy Depends on Conditioning Assumptions
Carola Engelke, Katja Heinisch, Christoph Schult
IWH Discussion Papers,
Nr. 18,
2019
Abstract
This paper examines the extent to which errors in economic forecasts are driven by initial assumptions that prove to be incorrect ex post. Therefore, we construct a new data set comprising an unbalanced panel of annual forecasts from different institutions forecasting German GDP and the underlying assumptions. We explicitly control for different forecast horizons to proxy the information available at the release date. Over 75% of squared errors of the GDP forecast comove with the squared errors in their underlying assumptions. The root mean squared forecast error for GDP in our regression sample of 1.52% could be reduced to 1.13% by setting all assumption errors to zero. This implies that the accuracy of the assumptions is of great importance and that forecasters should reveal the framework of their assumptions in order to obtain useful policy recommendations based on economic forecasts.
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