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The EU Commission proposed a regulation on artificial intelligence (AI) on 21 April 2021, which categorizes the use of AI in “social credit” as a prohibited application. This paper examines the definition and structure of the Social Credit System in China, which comprises various systems operating at different levels and sectors. The analysis focuses on two main subsystems: the database and one-stop inquiry platform for financial credit records, and the social governance tool designed to facilitate legal and political compliance. The development of the commercial customer credit reference is also explored. This paper further discusses the impacts and concerns associated with the implementation of the Chinese social credit system to raise awareness. The objective is to offer insights from the existing system and contribute to the ongoing discussion on regulating AI applications in social credit within the EU.
Experiments are an important tool in economic research. However, it is unclear to which extent the control of experiments extends to the perceptions subjects form of such experimental decision situations. This paper is the first to explicitly elicit perceptions of the dictator and trust game and shows that there is substantial heterogeneity in how subjects perceive the same game. Moreover, game perceptions depend not only on the game itself but also on the order of games (i.e., the broader experimental context in which the game is embedded) and the subject herself. This highlights that the control of experiments does not necessarily extend to game perceptions. The paper also demonstrates that perceptions are correlated with game behavior and moderate the relationship between game behavior and field behavior, thereby underscoring the importance and relevance of game perceptions for economic research.
This paper shows that support for climate action is high across survey participants from all EU countries in three dimensions: (1) Participants are willing to contribute personally to combating climate change, (2) they approve of pro-climate social norms, and (3) they demand government action. In addition, there is a significant perception gap where individuals underestimate others' willingness to contribute to climate action by over 10 percentage points, influencing their own willingness to act. Policymakers should recognize the broad support for climate action among European citizens and communicate this effectively to counteract the vocal minority opposed to it.
In recent decades, biodiversity has declined significantly, threatening ecosystem services that are vital to society and the economy. Despite the growing recognition of biodiversity risks, the private sector response remains limited, leaving a significant financing gap. The paper therefore describes market-based solutions to bridge the financing gap, which can follow a risk assessment approach and an impact-oriented perspective. Key obstacles to mobilising private capital for biodiversity conservation are related to pricing biodiversity due to its local dimension, the lack of standardized metrics for valuation and still insufficient data reporting by companies hindering informed investment decisions. Financing biodiversity projects poses another challenge, mainly due to a mismatch between investor needs and available projects, for example in terms of project timeframes and their additionality.
The development of China’s exports – is there a decoupling from the EU and the United States?
(2024)
Some observers warn that a high level of economic dependence on China could negatively affect the economic resilience of Western economies and therefore recommend reducing such dependence by gradually decoupling from China. On the other hand, industry leaders emphasise the economic importance of China and warn against any kind of trade conflicts.
Against this background, we briefly analyse the development of China’s export strategy. We find that the export intensity of the Chinese economy is diminishing and that exports are becoming more diversified overall. In addition, the relative importance of the United States and the European Union as export markets has been reduced, indicating a gradual decoupling of China from Western economies. Conversely, we find that exports to China have become more important, both for the EU and the United States. Although the figures remain at a non-critical level, Europe’s export activities could be more diversified as well.
How does the design of debt repayment schedules affect household borrowing? To answer this question, we exploit a Swedish policy reform that eliminated interest-only mortgages for loan-to-value ratios above 50%. We document substantial bunching at the threshold, leading to 5% lower borrowing. Wealthy borrowers drive the results, challenging credit constraints as the primary explanation. We develop a model to evaluate the mechanisms driving household behavior and find that much of the effect comes from households experiencing ongoing flow disutility to amortization payments. Our results indicate that mortgage contracts with low initial payments substantially increase household borrowing and lifetime interest costs.
We educate investors with significant dividend holdings about the benefits of dividend reinvestment and the costs of misperceiving dividends as additional, free income. The intervention increases planned dividend reinvestment in survey responses. Using trading records, we observe a corresponding causal increase in dividend reinvestment in the field of roughly 50 cents for every euro received. This holds relative to their prior behavior and a placebo sample. Investors who learned the most from the intervention update their trading by the largest extent. The results suggest the free dividends fallacy is a significant source of dividend demand. Our study demonstrates that simple, targeted, and focused educational interventions can affect investment behavior.
Inflation and trading
(2024)
We study how investors respond to inflation combining a customized survey experiment with trading data at a time of historically high inflation. Investors' beliefs about the stock return-inflation relation are very heterogeneous in the cross section and on average too optimistic. Moreover, many investors appear unaware of inflation-hedging strategies despite being otherwise well-informed about inflation and asset returns. Consequently, whereas exogenous shifts in inflation expectations do not impact return expectations, information on past returns during periods of high inflation leads to negative updating about the perceived stock-return impact of inflation, which feeds into return expectations and subsequent actual trading behavior.
This paper contributes a multivariate forecasting comparison between structural models and Machine-Learning-based tools. Specifically, a fully connected feed forward non-linear autoregressive neural network (ANN) is contrasted to a well established dynamic stochastic general equilibrium (DSGE) model, a Bayesian vector autoregression (BVAR) using optimized priors as well as Greenbook and SPF forecasts. Model estimation and forecasting is based on an expanding window scheme using quarterly U.S. real-time data (1964Q2:2020Q3) for 8 macroeconomic time series (GDP, inflation, federal funds rate, spread, consumption, investment, wage, hours worked), allowing for up to 8 quarter ahead forecasts. The results show that the BVAR improves forecasts compared to the DSGE model, however there is evidence for an overall improvement of predictions when relying on ANN, or including them in a weighted average. Especially, ANN-based inflation forecasts improve other predictions by up to 50%. These results indicate that nonlinear data-driven ANNs are a useful method when it comes to macroeconomic forecasting.
Central bank intervention in the form of quantitative easing (QE) during times of low interest rates is a controversial topic. The author introduces a novel approach to study the effectiveness of such unconventional measures. Using U.S. data on six key financial and macroeconomic variables between 1990 and 2015, the economy is estimated by artificial neural networks. Historical counterfactual analyses show that real effects are less pronounced than yield effects.
Disentangling the effects of the individual asset purchase programs, impulse response functions provide evidence for QE being less effective the more the crisis is overcome. The peak effects of all QE interventions during the Financial Crisis only amounts to 1.3 pp for GDP growth and 0.6 pp for inflation respectively. Hence, the time as well as the volume of the interventions should be deliberated.