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Monetary incentives, such as subsidies or bonuses, are often considered as a way to foster contributions to public goods in society and firms. This paper investigates experimentally the effect of private contribution incentives in the presence of a norm enforcement mechanism. Norm enforcement through peer punishment has been shown to be effective in raising contributions by itself. We test whether and how (centrally provided) private incentives interact with (decentralized) punishment, both of which affect subjects' monetary payoffs. The results of our experiment show that private incentives for contributors can reduce the effectiveness of the norm enforcement mechanism: Free riders are punished less harshly in the treatment with incentives, and as a consequence, average contributions to the public good are no higher than without incentives. This finding ties to and extends previous research on settings in which monetary incentives may fail to have the desired effect.

This paper analyzes efficiency and profitability in the Swiss banking sector over the period 1997–2019. We find strong evidence for scale economies: for most banks in the sample, efficiency and profitability increase with bank size. Using an instrumental variables strategy for a subset of geographically restrained banks, we find that the effect of size on efficiency and profitability is likely causal. Scale economies have been more pronounced since 2010 than in the years prior to the global financial crisis. There is little evidence for scale economies for the largest (systemically important) banks; their relatively lower efficiency and lower profitability appear driven by certain aspects of their business model. Our results further indicate that good capitalization and high efficiency and profitability are compatible.

The endowment effect is among the best known findings in behavioral economics and has been used as evidence for theories of reference-dependent preferences and loss aversion. However, a recent literature has questioned the robustness of the effect in the laboratory, as well as its relevance in the field. In this review, we provide a summary of the evidence and describe recent theoretical developments that can potentially reconcile the different findings, with a focus on expectation-based reference points. We also survey recent work from psychology that provides either alternatives to or refinements of the usual loss-aversion explanation. We argue that loss aversion is still the leading paradigm for understanding the endowment effect, but given the rich psychology behind the effect, a version of the theory that encompasses multiple reference points may be required.

Technology-based (“FinTech”) lenders increased their market share of U.S. mortgage lending from 2% to 8% from 2010 to 2016. Using loan-level data on mortgage applications and originations, we show that FinTech lenders process mortgage applications 20% faster than other lenders, controlling for observable characteristics. Faster processing does not come at the cost of higher defaults. FinTech lenders adjust supply more elastically than do other lenders in response to exogenous mortgage demand shocks. In areas with more FinTech lending, borrowers refinance more, especially when it is in their interest. We find no evidence that FinTech lenders target borrowers with low access to finance.

Fixed-rate mortgages (FRMs) dominate the U.S. mortgage market, with important consequences for monetary policy, household risk management, and financial stability. We show that the FRM market share is sharply lower when mortgages are difficult to securitize, exploiting plausibly exogenous variation in access to liquid securitization markets generated by a regulatory cutoff and time variation in private securitization activity. We interpret our findings as evidence that lenders are reluctant to retain the prepayment and interest rate risk embedded in FRMs. The form of securitization (private versus government backed) has little effect on FRM supply during periods in which private securitization markets are well functioning.

Do laboratory subjects correctly perceive the dynamics of a mean-reverting time series? In our experiment, subjects receive historical data and make forecasts at different horizons. The time series process that we use features short-run momentum and long-run partial mean reversion. Half of the subjects see a version of this process in which the momentum and partial mean reversion unfold over ten periods (“fast”), while the other subjects see a version with dynamics that unfold over 50 periods (“slow”). Typical subjects recognize most of the mean reversion of the fast process and none of the mean reversion of the slow process.

Home price expectations are believed to play an important role in housing dynamics, yet we have limited understanding of how they are formed and how they affect behaviour. Using a unique “information experiment” embedded in an online survey, this article investigates how consumers’ home price expectations respond to past home price growth, and how they impact investment decisions. After eliciting respondents’ priors about past and future local home price changes, we present a random subset of them with factual information about past (one- or five-year) changes, and then re-elicit expectations. This unique “panel” data allows us to identify causal effects of the information, and provides insights on the expectation formation process. We find that, on average, year-ahead home price expectations are revised in a way consistent with short-term momentum in home price growth, though respondents tend to underpredict the strength of momentum. Revisions of longer-term expectations show that respondents do not expect the empirically-occurring mean reversion in home price growth. These patterns are in line with recent behavioural models of housing cycles. Finally, we show that home price expectations causally affect investment decisions in a portfolio choice experiment embedded in the survey.

We argue that the time-varying regional distribution of housing equity influences the aggregate consequences of monetary policy through its effects on mortgage refinancing. Using detailed loan-level data, we show that regional differences in housing equity affect refinancing and spending responses to interest rate cuts, but these effects vary over time with changes in the regional distribution of house price growth. We build a heterogeneous household model of refinancing with mortgage borrowers and lenders and use it to explore the monetary policy implications arising from our regional evidence. We find that the 2008 equity distribution made spending in depressed regions less responsive to interest rate cuts, thus dampening aggregate stimulus and increasing regional consumption inequality, whereas the opposite occurred in some earlier recessions. Taken together, our results strongly suggest that monetary policy makers should track the regional distribution of equity over time.

Measuring the sensitivity of housing demand to mortgage rates and available leverage is challenging because there is generally no exogenous variation in these variables. This paper circumvents this issue by designing a strategic survey in which respondents report their willingness to pay (WTP) for a home under different financing scenarios. Relaxation of down payment constraints or an exogenous increase in nonhousing wealth has large effects on WTP, especially for poorer and more credit-constrained households. However, changing the mortgage rate has only moderate effects on WTP. These findings have implications for theoretical models of house price determination and for policy.

We use quasi-random access to the Home Affordable Refinance Program (HARP) to identify the causal effect of refinancing into a lower-rate mortgage on borrower balance sheet outcomes. Refinancing substantially reduces borrower default rates on mortgages and other debt. Refinancing also causes borrowers to expand their use of debt instruments, such as auto loans, home equity lines, and other consumer debts that are proxies for spending. Borrowers that appear more constrained ex ante grow these debts more strongly after refinancing but also pay down credit card balances by more. These borrowers also have lower take-up of the refinancing opportunity.