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Exploiting heterogeneity in U.S. firms' exposure to an unconventional monetary policy shock that reduced debt financing costs, I identify the impact of financing conditions on firms' toxic emissions. I find robust evidence that lower financing costs reduce toxic emissions and boost investments in emission reduction activities, especially capital-intensive pollution control activities. The effect is stronger for firms in noncompliance with environmental regulation. Examining the ability of regaining regulatory compliance by implementing pollution control activities I find that only capital-intensive activities help firms regaining compliance. These findings underscore the impact of firms' financing conditions for emissions and the environment.
We show that "quasi-dark" trading venues, i.e., markets with somewhat non-transparent trading mechanisms, are important parts of modern equity market structure alongside lit markets and dark pools. Using the European MiFID II regulation as a quasi-natural experiment, we find that dark pool bans lead to (i) volume spill-overs into quasi-dark trading mechanisms including periodic auctions and order internalization systems; (ii) little volume returning to transparent public markets; and consequently, (iii) a negligible impact on market liquidity and short-term price efficiency. These results show that quasi-dark markets serve as close substitutes for dark pools and consequently mitigate the effectiveness of dark pool regulation. Our findings highlight the need for a broader approach to transparency regulation in modern markets that takes into consideration the many alternative forms of quasi-dark trading.
We study the effects of market incompleteness on speculation, investor survival, and asset pricing moments, when investors disagree about the likelihood of jumps and have recursive preferences. We consider two models. In a model with jumps in aggregate consumption, incompleteness barely matters, since the consumption claim resembles an insurance product against jump risk and effectively reproduces approximate spanning. In a long-run risk model with jumps in the long-run growth rate, market incompleteness affects speculation, and investor survival. Jump and diffusive risks are more balanced regarding their importance and, therefore, the consumption claim cannot reproduce approximate spanning.
In this exploratory article, we consider the future of Deutsche Bank and Commerzbank and develop a new approach to the topic: instead of a merger of DB and CB we propose to consider a partial merger of the IT and related back office functions in order to create the basis for an Open Banking platform in Germany. Such a platform would act as a cross-institutional infrastructure company in which the participating banks develop a common data and IT platform (while respecting the data protection regulations). Significant parts of the transaction processes would be pooled by the institutions and executed by the Open Banking platform. Moreover, the institutions remain legally independent and compete with each other at the level of products and services that are developed and produced using just this common data and IT platform – “national champions” would not be created.
But such an “Open Banking Platform” could become even the nucleus of a European Banking platform that could be competitive with existing global data platforms from the USA and China which are already offering financial services and are likely to expand their offerings in the foreseeable future. The proposed model of an open data platform for banks prevents the emergence of national champions and supports the main goal of the banking union: creation of a financial system, in which single banks can be resolved without provoking a systemic crisis and forcing taxpayers to finance bailouts.
Decisions under ambiguity depend on both the belief regarding possible scenarios and the attitude towards ambiguity. This paper exclusively investigates the belief formation and belief updating process under ambiguity, using laboratory experiments. The results show that half of the subjects tend to adopt a simple heuristic strategy when updating beliefs, while the other half seems to partially adopt the Bayesian updates. We recover beliefs, represented by distributions of the priors/posteriors. The recoverable initial priors mostly follow a uniform distribution. We also find that subjects on average demonstrate slight pessimism in an ambiguous environment.
Do household inflation expectations affect consumption-savings decisions? We link survey data on quantitative inflation expectations to administrative data on income and wealth. We document that households with higher inflation expectations save less. Estimating panel data models with year and household fixed effects, we find that a one percentage point increase in a household's inflation expectation over time is associated with a 250-400 euro reduction in the household's change in net worth per year on average. We also document that households with higher inflation expectations are more likely to acquire a car and acquire higher-value cars. In addition, we provide a quantitative model of household-level inflation expectations.
We propose a simple modification of the time series filter by Hamilton (2018) that yields reliable and economically meaningful real-time output gap estimates. The original filter relies on 8-quarter-ahead forecast errors of a simple autoregression of log real GDP. While this approach yields a cyclical component of GDP that is hardly revised with new incoming data due to the one-sided filtering approach, it does not cover typical business cycle frequencies evenly, but short business cycles are muted and medium length business cycles are amplified. Further, the estimated trend is as volatile as GDP itself and can thus hardly be interpreted as potential GDP. A simple modification that is based on the mean of 4- to 12-quarter-ahead forecast errors shares the favorable real-time properties of the Hamilton filter, but leads to a much better coverage of typical business cycle frequencies and a smooth estimated trend. Based on output growth and inflation forecasts and a comparison to revised output gap estimates from policy institutions, we find that real-time output gaps based on the modified Hamilton filter are economically much more meaningful measures of the business cycle than those based on other simple statistical trend-cycle decomposition techniques such as the HP or the Bandpass filter.
We analyze cyclical co-movement in credit, house prices, equity prices, and longterm interest rates across 17 advanced economies. Using a time-varying multi-level dynamic factor model and more than 130 years of data, we analyze the dynamics of co-movement at different levels of aggregation and compare recent developments to earlier episodes such as the early era of financial globalization from 1880 to 1913 and the Great Depression. We find that joint global dynamics across various financial quantities and prices as well as variable-specific global co-movements are important to explain fluctuations in the data. From a historical perspective, global co-movement in financial variables is not a new phenomenon, but its importance has increased for some variables since the 1980s. For equity prices, global cycles play currently a historically unprecedented role, explaining more than half of the fluctuations in the data. Global cycles in credit and housing have become much more pronounced and longer, but their importance in explaining dynamics has only increased for some economies including the US, the UK and Nordic European countries. We also include GDP in the analysis and find an increasing role for a global business cycle.
There is substantial disagreement about the consequences of the Tax Cuts and Jobs Act (TCJA) of 2017, which constitutes the most extensive tax reform in the United States in more than 30 years. Using a large-scale two-country dynamic general equilibrium model with nominal rigidities, we find that the TCJA increases GDP by about 2% in the medium-run and by about 2.5% in the long-run. The shortrun impact depends crucially on the degree and costs of variable capital utilization, with GDP effects ranging from 1 to 3%. At the same time, the TCJA does not pay for itself. In our analysis, the reform decreases tax revenues and raises the debt-to-GDP ratio by about 15 percentage points in the medium-run until 2025. We show that combining the TCJA with spending cuts can dampen the increase in government indebtedness without reducing its expansionary effect.
Job loss expectations, durable consumption and household finances : evidence from linked survey data
(2019)
Job security is important for durable consumption and household savings. Using surveys, workers express a probability that they will lose their job in the next 12 months. In order to assess the empirical content of these probabilities, we link survey data to administrative data with labor market outcomes. Workers predict job loss quite well, in particular those whose job loss is followed by unemployment. Workers with higher job loss expectations acquire cheaper cars, and are less likely to buy new cars. In line with models of precautionary saving, higher job loss expectations are associated with more savings and less exposure to risky assets.