This paper investigates whether managers’ personal connections help corporate productivity to recover after a negative economic shock. Leveraging the heterogeneity in the severity of the financial crisis across different sectors, the paper reports that (i) the financial crisis had a negative effect on within-firm productivity, (ii) the effect was long-lasting and persistent, supporting a productivity-hysteresis hypothesis, and (iii) managers’ personal connections allowed corporations to recover from this productivity slowdown. Among the possible mechanisms, we show that connected managers operating in affected sectors foster productivity recovery through higher input cost efficiency and better access to the credit market, as well as more efficient use of labour and capital.

The economy is a complex system because market participants do not act independently but adjust their behavior to other agents and to the outcome which emerges from their joint actions (Arthur, 2014). Dependencies among participants can impede policy makers capabilities to influence or steer the course of the economy. Kambhu et al. (2007) argue that to influence developments in financial markets, for instance to prevent crises from spreading, there are only “coarse or indirect options” available for policy makers. Similar to crises which propagate through a complex system, interventions might result in unintended side effects which can also disseminate through the system. Thus, in a complex system, unintended consequences of policy efforts may well be the rule. Policy makers try to ward off or mitigate negative consequences for the economy and society during periods of crisis. For instance, during the Covid crisis large scale support programs for firms in Western economies were set up to avoid bankruptcies. Similarly, during the sovereign debt crisis in the Eurozone, the European Central Bank (ECB) set up large scale asset purchase programs as well as additionally longer-term refinancing operations (LTRO) which provided immediate support to financial market participants’ liquidity positions and thereby prevented a melt-down of the financial system. During these periods, immediate and abundant liquidity supply is of utmost importance. Meanwhile, crisis measures, due to their massive scale and non-specific target group, may entail unknown or unintended side effects for instance on competition among market participants, firms’ investment behavior, or changes in lending strategies and risk taking behavior of banks. Likewise, new regulatory frameworks such as the introduction of new markets can have consequences previously not thought of. For policy makers it is important to know direct effects of policy interventions but also to be aware of the possibility and impact of indirect or unexpected side effects in order to evaluate measures taken and to learn for future design of regulation or intervention.

We assess the cleansing effects of the 2008–2009 financial crisis. U.S. regions with higher levels of supervisory forbearance on distressed banks see less restructuring in the real sector: fewer establishments, firms, and jobs are lost when more distressed banks remain in business. In these regions, the banking sector has been less healthy for several years after the crisis. Regions with less forbearance experience higher productivity growth after the crisis with more firm entries, job creation, and employment, wages, patents, and output growth. Forbearance is greater for state-chartered banks and in regions with weaker banking competition and more independent banks.

Syndicated loan data provided by DealScan is an essential input in banking research. This data is rich enough to answer urging questions on bank lending, e.g., in the presence of financial shocks or climate change. However, many data options raise the question of how to choose the estimation sample. We employ a standard regression framework analyzing bank lending during the financial crisis of 2007/08 to study how conventional but varying usages of DealScan affect the estimates. The key finding is that the direction of coefficients remains relatively robust. However, statistical significance depends on the data and sampling choice and we provide guidelines for applied research.

Studies find that during the 2007–2009 global financial crisis, loan spreads rose and corporate lending tightened, especially for foreign borrowers (a flight-home effect). We find that banks in countries with explicit deposit insurance (DI) made smaller reductions in total lending and foreign lending, experienced smaller increases in loan spreads, and had quicker post-crisis recoveries. These effects are more pronounced for banks heavily relying on deposit funding. Evidence also reveals that more generous or credible DI design is associated with a stronger stabilization effect on bank lending during the crisis, confirmed by the difference-in-differences analysis based on expansion of DI coverage during the crisis. The stabilization effect is robust to the use of country-specific crisis measures and control of temporary government guarantees.

This paper generates a technical optimum of bank liquidity creation benchmark by tracing an efficient frontier in liquidity creation (bank intermediation) and questions why some banks are more efficient than others in such activities. Evidence reveals that medium size banks are most correlated to efficient frontier. Small (large) banks—focused on traditional banking activities—are found to be the most (least) efficient in creating liquidity in on-balance sheet items whereas large banks—involved in non-traditional activities—are found to be most efficient in off-balance sheet liquidity creation. Additionally, the liquidity efficiency of small banks is more resilient during the 2007-2008 financial crisis relative to other banks.

Der Rückgang der Wirtschaftsleistung im vierten Quartal 2021 konnte trotz eines Zuwachses im ersten Quartal 2022 noch nicht wieder ausgeglichen werden. Das Bruttoinlandsprodukt stieg nur leicht um 0,2%, allerdings dürfte die geringe Dynamik vorrangig pandemiebedingt getrieben sein. Die Folgen der kriegsbedingten Sanktionen dürften ab dem zweiten Quartal spürbar werden. Hinzu kommen erneute harte Lockdowns in China, welche die Lieferkettenprobleme verschärfen und den weltweiten Inflationsdruck hochhalten werden. Beide Faktoren treffen die deutsche Wirtschaft hart, und somit dürfte in den nächsten beiden Quartalen kaum mehr als eine Stagnation zu erwarten sein. Insgesamt wird die Wirtschaft in Deutschland laut IWH-Flash-Indikator im zweiten Quartal 2022 um knapp 0,1% zurückgehen und im dritten Quartal 2022 um 0,2% zulegen (vgl. Abbildung 1).

Die deutsche Wirtschaft steuert durch schwieriges Fahrwasser. Die Auftriebskräfte durch den Wegfall der Pandemiebeschränkungen, die Nachwehen der Coronakrise und die Schockwellen durch den Krieg in der Ukraine sorgen für gegenläufige konjunkturelle Strömungen. Allen Einflüssen gemeinsam ist ihre preistreibende Wirkung.

Confidence in the Phillips Curve (PC) as predictor of inflation developments along the business cycle has been shaken by recent “inflation puzzles” in advanced countries, such as the “missing disinflation” in the aftermath of the Great Recession and the “missing inflation” in the years of recovery, to which the Euro-Zone “excess deflation” during the post-crisis depression may be added. This paper proposes a newly specified Phillips Curve model, in which expected inflation, instead of being treated as an exogenous explanatory variable of actual inflation, is endogenized. The idea is simply that if the PC is used to foresee inflation, then its expectational component should in some way be the result of agents using the PC itself. As a consequence, the truly independent explanatory variables of inflation turn out to be the output gaps and the related forecast errors by agents, with notable empirical consequences. The model is tested with the Euro-Zone data 1999–2019 showing that it may provide a consistent explanation of the “inflation puzzles” by disentangling the structural component from the expectational effects of the PC.