Gender, Credit, and Firm Outcomes
Manthos D. Delis, Iftekhar Hasan, Maria Iosifidi, Steven Ongena
Journal of Financial and Quantitative Analysis,
Nr. 1,
2022
Abstract
Small and micro enterprises are usually majority-owned by entrepreneurs. Using a unique sample of loan applications from such firms, we study the role of owners’ gender in bank credit decisions and post-credit-decision firm outcomes. We find that, ceteris paribus, female entrepreneurs are more prudent loan applicants than are males, since they are less likely to apply for credit or to default after loan origination. The relatively more aggressive behavior of male applicants pays off, however, in terms of higher average firm performance after loan origination.
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A Comparison of Monthly Global Indicators for Forecasting Growth
Christiane Baumeister, Pierre Guérin
International Journal of Forecasting,
Nr. 3,
2021
Abstract
This paper evaluates the predictive content of a set of alternative monthly indicators of global economic activity for nowcasting and forecasting quarterly world real GDP growth using mixed-frequency models. It shows that a recently proposed indicator that covers multiple dimensions of the global economy consistently produces substantial improvements in forecasting accuracy, while other monthly measures have more mixed success. Specifically, the best-performing model yields impressive gains with MSPE reductions of up to 34% at short horizons and up to 13% at long horizons relative to an autoregressive benchmark. The global economic conditions indicator also contains valuable information for assessing the current and future state of the economy for a set of individual countries and groups of countries. This indicator is used to track the evolution of the nowcasts for the U.S., the OECD area, and the world economy during the COVID-19 pandemic and the main factors that drive the nowcasts are quantified.
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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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Loan Syndication under Basel II: How Do Firm Credit Ratings Affect the Cost of Credit?
Iftekhar Hasan, Suk-Joong Kim, Panagiotis Politsidis, Eliza Wu
Journal of International Financial Markets, Institutions and Money,
May
2021
Abstract
This paper investigates how syndicated lenders react to borrowers’ rating changes under heterogeneous conditions and different regulatory regimes. Our findings suggest that corporate downgrades that increase capital requirements for lending banks under the Basel II framework are associated with increased loan spreads and deteriorating non-price loan terms relative to downgrades that do not affect capital requirements. Ratings exert an asymmetric impact on loan spreads, as these remain unresponsive to rating upgrades, even when the latter are associated with a reduction in risk weights for corporate loans. The increase in firm borrowing costs is mitigated in the presence of previous bank-firm lending relationships and for borrowers with relatively strong performance, high cash flows and low leverage.
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Benchmarking New Zealand's Frontier Firms
Guanyu Zheng, Hoang Minh Duy, Gail Pacheco
IWH-CompNet Discussion Papers,
Nr. 1,
2021
Abstract
New Zealand has experienced poor productivity performance over the last two decades. Factors often cited as reasons behind this are the small size of the domestic market and distance to international partners and markets. While the distance reason is one that is fairly insurmountable, there are a number of other small advanced economies that also face similar domestic market constraints. This study compares the relative performance of New Zealand’s firms to those economies using novel cross-country microdata from CompNet. We present stylised facts for New Zealand relative to the economies of Belgium, Denmark, Finland, Netherlands and Sweden based on average productivity levels, as well as benchmarking laggard, median and frontier firms. This research also employs an analytical framework of technology diffusion to evaluate the extent of productivity convergence, and the impact of the productivity frontier on non-frontier firm performance. Additionally, both labour and capital resource allocation are compared between New Zealand and the other small advanced economies. Results show that New Zealand’s firms have comparatively low productivity levels and that its frontier firms are not benefiting from the diffusion of best technologies outside the nation. Furthermore, there is evidence of labour misallocation in New Zealand based on less labour-productive firms having disproportionally larger employment shares than their more productive counterparts. Counter-factual analysis illustrates that improving both technology diffusion from abroad toward New Zealand’s frontier firms, and labour allocation across firms within New Zealand will see sizable productivity gains in New Zealand.
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Optimizing Policymakers’ Loss Functions in Crisis Prediction: Before, Within or After?
Peter Sarlin, Gregor von Schweinitz
Macroeconomic Dynamics,
Nr. 1,
2021
Abstract
Recurring financial instabilities have led policymakers to rely on early-warning models to signal financial vulnerabilities. These models rely on ex-post optimization of signaling thresholds on crisis probabilities accounting for preferences between forecast errors, but come with the crucial drawback of unstable thresholds in recursive estimations. We propose two alternatives for threshold setting with similar or better out-of-sample performance: (i) including preferences in the estimation itself and (ii) setting thresholds ex-ante according to preferences only. Given probabilistic model output, it is intuitive that a decision rule is independent of the data or model specification, as thresholds on probabilities represent a willingness to issue a false alarm vis-à-vis missing a crisis. We provide real-world and simulation evidence that this simplification results in stable thresholds, while keeping or improving on out-of-sample performance. Our solution is not restricted to binary-choice models, but directly transferable to the signaling approach and all probabilistic early-warning models.
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Should Forecasters Use Real‐time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence
Katja Heinisch, Rolf Scheufele
German Economic Review,
Nr. 4,
2019
Abstract
In this paper, we investigate whether differences exist among forecasts using real‐time or latest‐available data to predict gross domestic product (GDP). We employ mixed‐frequency models and real‐time data to reassess the role of surveys and financial data relative to industrial production and orders in Germany. Although we find evidence that forecast characteristics based on real‐time and final data releases differ, we also observe minimal impacts on the relative forecasting performance of indicator models. However, when obtaining the optimal combination of soft and hard data, the use of final release data may understate the role of survey information.
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Gender Stereotypes still in MIND: Information on Relative Performance and Competition Entry
Sabrina Jeworrek
Journal of Behavioral and Experimental Economics,
October
2019
Abstract
By conducting a laboratory experiment, I test whether the gender tournament gap diminishes in its size after providing information on the relative performance of the two genders. Indeed, the gap shrinks sizeably, it even becomes statistically insignificant. Hence, individuals’ entry decisions seem to be driven not only by incorrect self-assessments in general but also by incorrect stereotypical beliefs about the genders’ average abilities. Overconfident men opt less often for the tournament and, thereby, increase their expected payoff. Overall efficiency, however, is not affected by the intervention.
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Expectation Formation, Financial Frictions, and Forecasting Performance of Dynamic Stochastic General Equilibrium Models
Oliver Holtemöller, Christoph Schult
Historical Social Research,
Special Issue: Governing by Numbers
2019
Abstract
In this paper, we document the forecasting performance of estimated basic dynamic stochastic general equilibrium (DSGE) models and compare this to extended versions which consider alternative expectation formation assumptions and financial frictions. We also show how standard model features, such as price and wage rigidities, contribute to forecasting performance. It turns out that neither alternative expectation formation behaviour nor financial frictions can systematically increase the forecasting performance of basic DSGE models. Financial frictions improve forecasts only during periods of financial crises. However, traditional price and wage rigidities systematically help to increase the forecasting performance.
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For How Long Do IMF Forecasts of World Economic Growth Stay Up-to-date?
Katja Heinisch, Axel Lindner
Applied Economics Letters,
Nr. 3,
2019
Abstract
This study analyses the performance of the International Monetary Fund (IMF) World Economic Outlook output forecasts for the world and for both the advanced economies and the emerging and developing economies. With a focus on the forecast for the current year and the next year, we examine the durability of IMF forecasts, looking at how much time has to pass so that IMF forecasts can be improved by using leading indicators with monthly updates. Using a real-time data set for GDP and for indicators, we find that some simple single-indicator forecasts on the basis of data that are available at higher frequency can significantly outperform the IMF forecasts as soon as the publication of the IMF’s Outlook is only a few months old. In particular, there is an obvious gain using leading indicators from January to March for the forecast of the current year.
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