The effects of private equity buyouts on employment, productivity, and job reallocation vary tremendously with macroeconomic and credit conditions, across private equity groups, and by type of buyout. We reach this conclusion by examining the most extensive database of U.S. buyouts ever compiled, encompassing thousands of buyout targets from 1980 to 2013 and millions of control firms. Employment shrinks 12% over two years after buyouts of publicly listed firms—on average, and relative to control firms—but expands 15% after buyouts of privately held firms. Postbuyout productivity gains at target firms are large on average and much larger yet for deals executed amid tight credit conditions. A postbuyout tightening of credit conditions or slowing of gross domestic product growth curtails employment growth and intrafirm job reallocation at target firms. We also show that buyout effects differ across the private equity groups that sponsor buyouts, and these differences persist over time at the group level. Rapid upscaling in deal flow at the group level brings lower employment growth at target firms. We relate these findings to theories of private equity that highlight agency problems at portfolio firms and within the private equity industry itself.

Spatial segregation of low- and high-wage workers is a persistent economic issue with broad social implications. Using social security data and an AKM wage decomposition, this paper examines spatial wage inequality in West Germany. Spatial inequality in log wages rose sharply between 1998 and 2008, mainly due to increased variance in worker pay premiums across regions (48%) and stronger positive spatial assortative matching of workers and establishments (40%), i.e. colocation. Changes in establishment wage premia are mostly unrelated to rising colocation whereas labor mobility even reduced it. Instead, growth in worker pay premiums among stayers was concentrated in regions where high-wage workers and high-wage establishments were overrepresented already in the 1990s and, thus, magnified pre-existing colocation leading to ‘colocation without relocation’. Germany’s rising trade surplus, especially with Eastern Europe, boosted stayers’ worker pay premiums in those ex-ante high-wage regions and fully explains rising colocation.

This study provides new evidence on the impact of the EU Cohesion Policy on income growth in less developed regions. Our panel includes data from all European regions for the years 1989-2020. Using a fuzzy Regression Discontinuity Design, we model treatment dynamics by applying a random effects estimator. Based on digitized historical data, we precisely replicate the policy rule and correctly classify the regions’ eligibility status. Results show that the policy has a moderate positive effect on GDP per capita growth in the targeted regions.

We exploit staggered real estate transaction tax (RETT) hikes across German states to identify the effect on the growth rates of regional house prices and outstanding mortgage loans by all local German banks. The results show that a RETT hike by one percentage point reduces regional house prices by 3%–4%. Furthermore, IV-regressions yield that a 1 percentage point drop in regional house prices induced by a RETT increase leads to a 0.3% decline in regional mortgage lending, particularly among low-capitalized banks in rural regions.

We investigate how global banks’ macroeconomic expectations for borrower countries influence their credit supply. Utilizing granular data on varying expectations among banks lending to the same firm at the same time, combined with an instrumental variable approach, we find that more optimistic GDP growth expectations for a borrower country are strongly linked to increased credit supply. Specifically, a one standard deviation increase in a lender’s GDP growth expectation for the borrower’s country corresponds to an increase of 8.46 percentage points in the loan share, equivalent to approximately 0.75 standard deviations of the loan share and $75.35 million in loan amount. In contrast, global banks’ short-term inflation expectations do not show a significant impact on their credit supply.

Accurate macroeconomic forecasts are essential for effective policy decisions, yet their precision depends on the accuracy of the underlying assumptions. This paper examines the extent to which assumption errors affect forecast accuracy, introducing the average squared assumption error (ASAE) as a valid instrument to address endogeneity. Using double/debiased machine learning (DML) techniques and partial linear instrumental variable (PLIV) models, we analyze GDP growth forecasts for Germany, conditioning on key exogenous variables such as oil price, exchange rate, and world trade. We find that traditional ordinary least squares (OLS) techniques systematically underestimate the influence of assumption errors, particularly with respect to world trade, while DML effectively mitigates endogeneity, reduces multicollinearity, and captures nonlinearities in the data. However, the effect of oil price assumption errors on GDP forecast errors remains ambiguous. These results underscore the importance of advanced econometric tools to improve the evaluation of macroeconomic forecasts.

The European Commission’s growth forecasts play a crucial role in shaping policies and provide a benchmark for many (national) forecasters. The annual forecasts are built on quarterly estimates, which do not receive much attention and are hardly known. Therefore, this paper provides a comprehensive analysis of multi-period ahead quarterly GDP growth forecasts for the European Union (EU), euro area, and several EU member states with respect to first-release and current-release data. Forecast revisions and forecast errors are analyzed, and the results show that the forecasts are not systematically biased. However, GDP forecasts for several member states tend to be overestimated at short-time horizons. Furthermore, the final forecast revision in the current quarter is generally downward biased for almost all countries. Overall, the differences in mean forecast errors are minor when using real-time data or pseudo-real-time data and these differences do not significantly impact the overall assessment of the forecasts’ quality. Additionally, the forecast performance varies across countries, with smaller countries and Central and Eastern European countries (CEECs) experiencing larger forecast errors. The paper provides evidence that there is still potential for improvement in forecasting techniques both for nowcasts but also forecasts up to eight quarters ahead. In the latter case, the performance of the mean forecast tends to be superior for many countries.

Utilizing near real-time QuickBooks data from over 1.6 million small businesses and a targeted survey, this paper highlights the critical role credit card financing plays for small business activity. We examine a two year period beginning in January of 2021. A turbulent period during which, credit card usage by small U.S. businesses nearly doubled, interest payments rose by 60%, and delinquencies reached 2.8%. We find, first, monthly credit card payments were up to three times higher than loan payments during this time. Second, we use targeted surveys of these small businesses to establish credit cards as a key financing source in response to firm-level shocks, such as uncertain cash flows and overdue invoices. Third, we establish the importance of credit cards as an important financial transmission mechanism. Following the Federal Reserve’s rate hikes in early 2022, banks cut credit card supply, leading to a 15.75% drop in balances and a 10% decline in revenue growth, as well as a 1.5% decrease in employment growth among U.S. small businesses. These higher rates also rendered interest payments unsustainable for many, contributing to half of the observed increase in delinquencies. Lastly, a simple heterogeneous firm model with a cash-in-hand constraint illustrates the significant macroeconomic impact of credit card financing on small business activity.

Lowering carbon intensity in manufacturing is necessary to transform current production technologies. We test if local agents’ preferences, revealed by vote shares for the Green party during local elections in Germany, relate to the carbon intensity of investments in production technologies. Our sample comprises all investment choices made by manufacturing establishments from 2005-2017. Our results suggest that ecological preferences correlate with significantly fewer carbon-intensive investment projects while investments stimulating growth and reducing carbon emissions increase by 14 percentage points. Both results are more distinct in federal states where the Green Party enjoys political power and local ecological preferences are high.

We analyze how creditor rights affect the nonsynchronicity of global corporate credit default swap spreads (CDS-NS). CDS-NS is negatively related to the country-level creditor-control rights, especially to the “restrictions on reorganization” component, where creditor-shareholder conflicts are high. The effect is concentrated in firms with high investment intensity, asset growth, information opacity, and risk. Pro-creditor bankruptcy reforms led to a decline in CDS-NS, indicating lower firm-specific idiosyncratic information being priced in credit markets. A strategic-disclosure incentive among debtors avoiding creditor intervention seems more dominant than the disciplining effect, suggesting how strengthening creditor rights affects power rebalancing between creditors and shareholders.