Capital Account Liberalisation Does Worsen Income Inequality
Xiang Li, Dan Su
IWH Discussion Papers,
No. 7,
2020
Abstract
This study examines the relationship between capital account liberalisation and income inequality. Adopting a novel identification strategy, namely a difference-in-difference estimation combined with propensity score matching between the liberalised and closed countries, we provide robust evidence that opening the capital account is associated with an adverse impact on income inequality in developing countries. The main findings are threefold. First, fully liberalising the capital account is associated with a small rise of 0.07-0.30 standard deviations in the Gini coefficient in the short-run and a rise as large as 0.32-0.62 standard deviations in the ten years after liberalisation, on average. Second, widening income inequality is the outcome of the growing income share of the rich at the cost of the poor. The long-term effect of capital account liberalisation includes a reduction in the income share of the poorest half by 2.66-3.79 percentage points and an increase in the income share of the richest 10% by 5.19-8.76 percentage points. Third, the directions and categories of capital account liberalisation matter. Inward capital account liberalisation is more detrimental to income equality than outward capital account liberalisation, and free access to the international equity market exacerbates income inequality the most, while foreign direct investment has an insignificant impact on inequality.
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How Does Economic Policy Uncertainty Affect Corporate Debt Maturity?
Xiang Li, Dan Su
IWH Discussion Papers,
No. 6,
2020
Abstract
This paper investigates whether and how economic policy uncertainty affects corporate debt maturity. Using a cross-country firm-level dataset for France, Germany, Spain, and Italy from 1996 to 2010, we find that an increase in economic policy uncertainty is significantly associated with a shortened debt maturity. Specifically, a 1% increase in economic policy uncertainty is associated with a 0.22% decrease in the long-term debt-to-assets ratio and a 0.08% decrease in debt maturity. Moreover, the impacts of economic policy uncertainty are stronger for innovation-intensive firms. We use firms‘ flexibility in changing debt maturity and the deviation to leverage target to gauge the causal relationship, and identify the reduced investment and steepened term structure as transmission mechanisms.
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Asymmetric Investment Responses to Firm-specific Forecast Errors
Julian Berner, Manuel Buchholz, Lena Tonzer
IWH Discussion Papers,
No. 5,
2020
Abstract
This paper analyses how firm-specific forecast errors derived from survey data of German manufacturing firms over 2007–2011 affect firms’ investment propensity. Understanding how forecast errors affect firm investment behaviour is key to mitigate economic downturns during and after crisis periods in which forecast errors tend to increase. Our findings reveal a negative impact of absolute forecast errors on investment. Strikingly, asymmetries arise depending on the size and direction of the forecast error. The investment propensity declines if the realised situation is worse than expected. However, firms do not adjust investment if the realised situation is better than expected suggesting that the uncertainty component of the forecast error counteracts positive effects of unexpectedly favorable business conditions. Given that the fraction of firms making positive forecast errors is higher after the peak of the recent financial crisis, this mechanism can be one explanation behind staggered economic growth and slow recovery following crises.
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Integrated Assessment of Epidemic and Economic Dynamics
Oliver Holtemöller
IWH Discussion Papers,
No. 4,
2020
Abstract
In this paper, a simple integrated model for the joint assessment of epidemic and economic dynamics is developed. The model can be used to discuss mitigation policies like shutdown and testing. Since epidemics cause output losses due to a reduced labor force, temporarily reducing economic activity in order to prevent future losses can be welfare enhancing. Mitigation policies help to keep the number of people requiring intensive medical care below the capacity of the health system. The optimal policy is a mixture of temporary partial shutdown and intensive testing and isolation of infectious persons for an extended period of time.
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flexpaneldid: A Stata Toolbox for Causal Analysis with Varying Treatment Time and Duration
Eva Dettmann, Alexander Giebler, Antje Weyh
IWH Discussion Papers,
No. 3,
2020
Abstract
The paper presents a modification of the matching and difference-in-differences approach of Heckman et al. (1998) for the staggered treatment adoption design and a Stata tool that implements the approach. This flexible conditional difference-in-differences approach is particularly useful for causal analysis of treatments with varying start dates and varying treatment durations. Introducing more flexibility enables the user to consider individual treatment periods for the treated observations and thus circumventing problems arising in canonical difference-in-differences approaches. The open-source flexpaneldid toolbox for Stata implements the developed approach and allows comprehensive robustness checks and quality tests. The core of the paper gives comprehensive examples to explain the use of the commands and its options on the basis of a publicly accessible data set.
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Financial Linkages and Sectoral Business Cycle Synchronisation: Evidence from Europe
Hannes Böhm, Julia Schaumburg, Lena Tonzer
IWH Discussion Papers,
No. 2,
2020
Abstract
We analyse whether financial integration between countries leads to converging or diverging business cycles using a dynamic spatial model. Our model allows for contemporaneous spillovers of shocks to GDP growth between countries that are financially integrated and delivers a scalar measure of the spillover intensity at each point in time. For a financial network of ten European countries from 1996-2017, we find that the spillover effects are positive on average but much larger during periods of financial stress, pointing towards stronger business cycle synchronisation. Dismantling GDP growth into value added growth of ten major industries, we observe that some sectors are strongly affected by positive spillovers (wholesale & retail trade, industrial production), others only to a weaker degree (agriculture, construction, finance), while more nationally influenced industries show no evidence for significant spillover effects (public administration, arts & entertainment, real estate).
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Intangible Capital and Productivity. Firm-level Evidence from German Manufacturing
Wolfhard Kaus, Viktor Slavtchev, Markus Zimmermann
IWH Discussion Papers,
No. 1,
2020
Abstract
We study the importance of intangible capital (R&D, software, patents) for the measurement of productivity using firm-level panel data from German manufacturing. We first document a number of facts on the evolution of intangible investment over time, and its distribution across firms. Aggregate intangible investment increased over time. However, the distribution of intangible investment, even more so than that of physical investment, is heavily right-skewed, with many firms investing nothing or little, and a few firms having very large intensities. Intangible investment is also lumpy. Firms that invest more intensively in intangibles (per capita or as sales share) also tend to be more productive. In a second step, we estimate production functions with and without intangible capital using recent control function approaches to account for the simultaneity of input choice and unobserved productivity shocks. We find a positive output elasticity for research and development (R&D) and, to a lesser extent, software and patent investment. Moreover, the production function estimates show substantial heterogeneity in the output elasticities across industries and firms. While intangible capital has small effects for firms with low intangible intensity, there are strong positive effects for high-intensity firms. Finally, including intangibles in a gross output production function reduces productivity dispersion (measured by the 90-10 decile range) on average by 3%, in some industries as much as nearly 9%.
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