This paper quantifies the consequences of a better match between decision-making and cost-bearing responsibilities in the provision of compulsory schooling in Switzerland. Specifically, I investigate whether the elimination of cost-sharing based on effective local expenditures for teachers sets incentives for cost-savings among municipalities. This hypothesis is tested through two local-level panel analyses in the Swiss cantons of Luzern and St.Gallen. The results provide empirical evidence that a substantial increase in the local cost share of teacher expenditures does, on average, not lead to an economically relevant and statistically significant reduction in municipal spending on teachers per student. However, the larger the municipality, the higher the estimated savings, which is evidence that small municipalities face only little scope for cost reductions because they are severely constrained by cantonal policies on class formation. I discuss several residual reasons that might account for limited consequences, including imperfect labor markets for teachers and the political economy of teacher employment.
Different consumption patterns have been linked to different levels of responsibility for current greenhouse gas (ghg) emissions, and it is well established that the affluent are responsible for higher levels of global ghg emission than are the poor. Here I couple a life cycle assessment of consumer goods with household survey data about consumption patterns to arrive at household level responsibility for global ghg emissions by consumption category. This allows me to provide a detailed analysis of how different consumption categories contribute to this responsibility. From this, I offer insights into how this information can be used for designing policies that create equitable outcomes. I conclude that the distributional impacts of ghg pricing with revenue recycling will remain unproblematic as climate policy continues to cover more ghgs from more regions. If it is desired that high-income households make a bigger contribution to the emissions reduction effort than others, focusing climate policy on transport (high confidence), eating out, and clothing (both with lower confidence) may provide avenues for achieving that. This is the case, since responsibility for ghg emissions from these consumption categories increases faster with income than it does for other goods.
The restaurant industry has a high failure rate and predicting restaurant bankruptcy is an important task to mitigate economic losses. Restaurant consumer review data contains rich information and influences future restaurant demand. We investigate the value of publicly available data for predicting bankruptcies of individual restaurants. Our unique data set includes alternative consumer data from the two most frequently used online restaurant platforms in Switzerland and official business data from Swiss government websites. In evaluating the accuracy of predictive bankruptcy probabilities, we quantify the potential of the alternative data sources and we analyze the relevance of novel predictor variables. We find that alternative consumer data is relevant for restaurant bankruptcy prediction and the highest prediction accuracy is achieved when alternative data and traditional business data are combined.
Using granular customs data, we construct a counterfactual of the evolution of Swiss goods exports under the premise that the minimum exchange rate policy would have been continued. We study the adjustment dynamics of aggregate and sectoral goods exports due to the exchange rate shock in January 2015 and examine potential differences between sectors. While Swiss total nominal exports drop in Swiss Franc, they increase in Euro. In real quantities, total exports remain largely unaffected indicating a high degree of resilience of the Swiss export industry. At the sectoral level, we observe a heterogeneous adjustment of exports consistent with varying degrees of supply-side adjustment flexibility.
There is an increasing demand for understanding how international shocks affect regions within a country differently. We study the short-term effects of a global energy price shock on output and inflation in the Swiss cantons using input–output techniques. Our results show that the induced inflation and contraction of output are small compared to other countries, indicating that Switzerland is generally resilient to price changes of fossil fuels. This is due to the low dependence of Switzerland on oil and gas and because of the large value added share of other activities. The responses of the cantons are heterogeneous, with Ticino, Neuchâtel and Basel-Country being most affected owing to their specialization in fossil fuel-dependent sectors with strong reliance on international inputs. Although the source of the responses to the shock relates to the energy sector, the contribution of other sectors through regional international linkages is larger as a result of an intermediates’ price spiral in all cantons. The results emphasize the informational gains from data on sectoral structures and global value chain integration at the regional level.
This paper proposes a new approach to calculating the credit gap: the deviation of the credit-to-GDP ratio from its long-run trend. Our method weights credit gap measures from different decomposition methods based on their out-of-sample forecasting performance. The results show that this weighted approach to estimating the credit gap outperforms other popular trend-cycle decomposition methods in predicting changes in the credit-to-GDP ratio. Furthermore, we also show that this combined credit gap measure can help mitigate the endpoint problem that is associated with conventional measures of credit gap.
Using novel survey data from Swiss firms, this paper empirically examines the relationship between the use of digital technologies and the prevalence of performance incentives. We argue that digital technologies tend to reduce the cost of organizational monitoring through improved measurement of employee behavior and performance, as well as through employee substitution in conjunction with a reduced agency problem. While we expect the former mechanism to increase the prevalence of performance incentives, the latter is likely to decrease it. Our doubly robust ATE estimates show that companies using business software and certain key technologies of Industry 4.0 increasingly resort to performance incentives, suggesting that the improved measurement effect dominates the employee substitution effect. In addition, we find that companies emerging as technology-friendly use performance incentives more frequently than their technology-averse counterparts. Both findings hold for managerial and non-managerial employees. Our estimation results are robust to a variety of sensitivity checks and suggest that Swiss businesses leverage digital technologies to enhance control over production or service processes, allowing them to intensify their management of employees through performance incentives.
We study the effects of a reform to VAT rules (the reverse charge mechanism on domestic transactions) aimed at eliminating VAT fraud involving cross-border transactions within the European Union (EU). The EU VAT system is prone to fraud involving cross-border transactions between member states, whereby traders either collect VAT without rightfully remitting it to tax authorities or claim a VAT refund to which they are not entitled. We find that pre-reform fraud amounts to around 4% of the trade volume of treated products, or 0.1–0.2% of overall VAT revenues in reform countries in the year leading to the reform. We also show that fraud is concentrated in countries with higher corruption, lower customs efficiency, and lower GDP per capita. Our results represent a lower bound for the gains from local fraud removal, which appears similar in magnitude to the costs incurred by firms to comply with the reform.
Fiscal rules are argued to be important for sound and sustainable fiscal policies and have been increasingly adopted over the last 20 years. As increased fiscal pressure and fiscal risks urge countries to address the public debt legacy left by recent economic crises, fiscal rules come under greater scrutiny. To inform the debate on fiscal frameworks, this paper presents a comprehensive survey of the empirical literature on the impact of fiscal rules. In particular, we discuss the recent empirical literature that investigates the impact of fiscal rules on various elements related to fiscal performance and beyond. Our survey finds that fiscal rules are associated with improved fiscal performance as approximated by improved budget balances, lower debt and lower public spending volatility. Furthermore, empirical research finds that fiscal rules are related to more accurate budget forecasts and improved sovereign bond ratings. From a macroeconomic perspective, well-designed fiscal rules do not principally undermine public investment, do not increase pro-cyclicality in fiscal policy-making and can support fiscal consolidations. These results, however, also depend on the broader economic and institutional context. Moreover, there is emerging literature that links fiscal rules to macroeconomic and broader political outcomes, such as income inequality and political polarisation. We discuss methodological challenges related to identification and point to avenues for future research.
Cableways alleviate access to the Alps and were crucial in establishing the skiing tourism boom of the after-war years. Moreover, cableway operators employ a large share of residents, are complemented by tourism-related services and are therefore a key economic pillar in otherwise laggard regions. We exploit comprehensive historical data of all ever-built cableways in Switzerland linked to income and population data to show how much ski area access benefits the municipalities’ economy compared to similar municipalities without such access on their territory. Evaluating difference-in-differences, we find that opening a ski area between 1940 and 1980 is related to economic growth that persists until today. Particularly, it attracted new residents and created more productive employment opportunities in tourism-related services, thereby raising incomes and tax revenues. Our results contribute to the debate of what economic risks municipalities with access to ski areas face once the decreasing snowpack forces a ski area to close.
This paper introduces a novel method to extract the sentiment embedded in the Management’s Discussion and Analysis (MD A) section of 10-K filings. The proposed method outperforms traditional approaches in terms of sentiment classification accuracy. Utilizing this method, the MD A sentiment is found to be a strong negative predictor of future stock returns, demonstrating consistency in both in-sample and out-of-sample settings. By contrast, if traditional sentiment extraction methods are used, the MD A sentiment exhibits no predictive ability for stock markets. Additionally, the MD A sentiment is associated with dividend-related macroeconomic channels regarding future stock return prediction.
Information friction makes it difficult for job seekers to find new employment opportunities. We propose a method for providing individual-specific occupation recommendations by ranking occupations based on their proximity to the worker’s profile. We identify a set of twelve skills, abilities and work styles that capture the worker-oriented requirements of all occupations and discuss how to measure these items using online questions and tasks. We use the Euclidean distance between the measured items pertaining to a worker and the requirements of an occupation to measure the proximity between job seekers and occupations. We show that the proximity between job seekers’ profiles and their preunemployment occupation predicts their intention to change occupations, thus suggesting that our method captures a meaningful conceptualization of mismatch. We also show that our method generates recommendations that differ from the previous occupations of mismatched job seekers, thereby potentially expanding their search scope.
In Cameroon, major inequalities exist in women’s access to antenatal care (ANC), yet underlying circumstance drivers remain understudied. Using recently available Demographic and Health Survey data, we conducted multilevel model and spatial analyses to identify circumstance factors driving ANC disparities across the country's diverse regions. Drawing on a novel integration of theoretical frameworks, we evaluated how circumstances like geographic, economic and educational barriers combined to shape inequities. Both Shapley and Fields decomposition techniques apportioned contributors to ongoing inequality. Results from our study provide the first direct comparison of these approaches in Cameroon, finding a strong positive correlation between methods. Our findings show that ANC utilization overall was suboptimal, varying substantially between urban and rural areas. Key circumstance factors which disproportionately constrained disadvantaged groups’ opportunities for care included household wealth, level of education of the woman and spouse, and place of residence. Policy-relevant insights emerge from disentangling multifaceted opportunity gaps. Targeted interventions should address modifiable barriers facing underserved populations to promote more equal maternal health nationwide. Our multidisciplinary analytical approach offers lessons for analysing complex health disparities in diverse low-resource settings. Graphical abstract
This paper quantifies empirically the macroeconomic and financial effects of Climate Policy Risk (CPR) in Switzerland. To do so, I develop a new CPR index using text analysis techniques on a large dataset of Swiss media articles. The identification of CPR shocks is achieved by using narrative restrictions around events which are likely to have coincided with an increase in the probability of adopting tighter climate policies. I find that CPR shocks are associated with a significant decline in real GDP and a decline in firm-level CO2 emissions. Using firm-level equity price data and rolling linear panel regressions, I document that CPR is increasingly reflected in asset prices. I further find that CO2-intensive firms perform significantly worse than their greener counterparts following events which increased transition risk. The results are in line with recent theoretical contributions.
This paper analyses how working from home affects workplace learning in terms of theoretical and practical knowledge during COVID19. We employ panel data gathered in monthly surveys of respondents in training companies between October 2020 and March 2022 to investigate this question. Apprentices in Switzerland are our case study. We address potential endogeneity concerns in two ways. First, we exploit variation across survey respondents and time in two-way fixed effects models. Second, we pursue an instrumental variable “shift-share”-type approach that leverages how occupations react to exogenous changes in working from home regulations. The results suggest that working from home has a significantly negative impact on practical knowledge but not theoretical knowledge, relative to frequenting the workplace. We do not find significant heterogeneity across company size. Similarly, our results do not vary significantly between occupations in which working from home is relatively more or less prevalent. Our findings remain robust to a wide range of robustness checks. Our evidence-based recommendations aim to preserve the acquisition of knowledge through workplace training.
Survey data can offer timely information on the current state of the economy and its short-term outlook. In this paper, we propose a “Swiss Economic Confidence Index” (SEC). This is a monthly indicator based on aggregating a selection of individual survey indicators, which we show to have favorable leading properties. Applying simple criteria, we select those surveys from a set of currently more than 250 sentiment indicators. We show that the SEC index provides useful signals on GDP growth in a number of real-time out-of-sample forecasting exercises.
During several weeks in the second half of the year 2020, the cantons of Switzerland could choose to adopt the government-determined facial-mask policy, corresponding to mandatory facial-mask wearing on public transport, or a strict facial-mask policy, corresponding to mandatory facial-mask wearing on public transport and in all public or shared spaces where social distancing was not possible. We estimate the effect of introducing the strict facial-mask policy on the spread of COVID-19 in Switzerland during this first phase of the pandemic in 2020, using the cantonal heterogeneity in facial-mask policies. We adjust for social distancing behavior, weather, other non-pharmaceutical policies and further variables. We estimate a significant reduction in the expected spread of COVID-19 in the early pandemic if the strict facial-mask policy is adopted.
The issuance of retail central bank digital currency (CBDC) involves a transfer of risk from commercial banks to the central bank. Mechanisms that limit the transfer of risk, such as an unattractive interest rate, a quantity ceiling or the non-convertibility of cash and reserves into CBDC, are likely to discourage the use of CBDC as a medium of exchange and thus defeat the purpose of issuing CBDC.
Correctly anticipating the earnings for different education profiles is pivotal in making informed education decisions. In this paper, leveraging unique survey data, we study the wage expectations for academic and vocational education backgrounds in Switzerland. Personal reference points matter in forming these wage expectations as we find significant heterogeneity in their distributions by gender, age, socioeconomic status, region of residence, and migration background. Asymmetries exist between beliefs for academic and vocational backgrounds since relative differences in wage expectations also vary by respondents’ characteristics. These heterogeneities are vital for education policy because our analyses show that the wage expectations are associated with preferences for specific educational tracks for the own (hypothetical) child. If education decisions are ill-informed, this possibly leads to educational mismatches and related adverse effects later in life.
The paper provides a disaggregated mixed frequency framework for the estimation of GDP. The GDP is disaggregated into components that can be forecasted based on information available at higher sampling frequency; i.e. monthly, weekly or daily. The model framework is applied for Greek GDP nowcasting. The results provide evidence that the more accurate nowcasting estimations require i) the disaggregation of GDP, ii) the use of a multilayer mixed frequency framework, iii) the inclusion of financial information on a daily frequency. The simulation study provides evidence in favor of the disaggregation into components despite the inclusion of multiple sources of forecast errors.
