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on Discrete Choice Models |
| By: | Lambrecht, Isabel B.; Rajiv, Sharanya; De Block, Wouter; Ergasheva, Tanzila; Maertens, Miet; Mardonova, Mohru; Van Hoyweghen, Kaat |
| Abstract: | Labor migration is often driven by a need for income, and can also be motivated by a desire for higher earnings. A naïve assumption is therefore that an increase in local livelihood alternatives might reduce outmigration, something which has been found to hold true in some settings, but not in others. This study employs a discrete choice experiment (DCE) with 408 rural respondents in Tajikistan—a country heavily reliant on remittances from abroad—to assess whether specific local income-generating opportunities, such as those offered through cash-for-work programs or through the provision of additional farmland, might affect stated preferences regarding migration. The study explores trade-offs between local income generating opportunities (wage employment, access to farmland, and irrigation infrastructure) and migration restrictions, i.e., hypothetical constraints on household members migrating abroad for a given duration. We rely on stated rather than revealed preferences to examine these trade-offs. Our findings lend some support to the idea that households are willing to accept outmigration restrictions in return for improved local income-generation opportunities, either through wage employment or own-farming. Yet, findings are heterogeneous and depend on the households’ current and anticipated reliance on labor migration. |
| Keywords: | migration; livelihoods; land; income transfers; remittances; public works; Tajikistan; Central Asia |
| Date: | 2026–04–24 |
| URL: | https://d.repec.org/n?u=RePEc:fpr:ifprid:182632 |
| By: | Omar Abdel Haq (Harvard Business School); Amitabh Chandra (Harvard Business School & Harvard Kennedy School); Tomáš Jagelka (University of Bonn, Dartmouth College, & CREST-Ensae); Erzo F.P. Luttmer (Dartmouth College); Joshua Schwartzstein (Harvard Business School) |
| Abstract: | Large Language Models (LLMs) are trained on a prodigious corpus of human writing and may reveal human preferences over characteristics of life courses, such as income, longevity, and working conditions. We present OpenAI's GPT-5.4 and a broadly representative sample of Americans with pairs of life stories and ask them to choose the life they would prefer for themselves. A person's choice is better predicted by the LLM's choice than by another person’s choice over the same stories, and LLM valuations of several life attributes are similar to those derived from human responses. Our results suggest that LLM responses offer a scalable and cost-effective complement to existing methods for studying human preferences. |
| Keywords: | Life preferences, LLMs, LLM revelation conjecture, life stories, essential life attributes, life attribute valuations |
| JEL: | D90 |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:ajk:ajkdps:410 |
| By: | Nobuyuki Hanaki; Bolin Mao; Tiffany Tsz Kwan Tse; Wenxin Zhou |
| Abstract: | This study investigates willingness to pay (WTP) for stock forecasting advice from algorithms, financial experts, and peers. In two incentivized forecasting experiments, participants purchased advice using an incentive-compatible mechanism and then decided how much to incorporate it into their forecasts. Participants assigned the highest WTP to algorithmic advice and relied on it as heavily as expert advice, despite its forecasting performance being no better than alternative sources. Consequently, participants overpaid for advice, especially algorithmic advice, whose realized benefits were insufficient to offset its cost. A second experiment shows that overpayment persists even after repeated opportunities to revise WTP with detailed feedback on advice quality and realized net benefits. The results suggest that individuals place excessive value on algorithmic advice perceived as sophisticated or credible, even when its realized economic value is limited. These findings highlight the importance of tools and disclosure policies that help individuals better assess the economic value of algorithmic advice. |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:dpr:wpaper:1268rr |
| By: | Omar Martin Fieles-Ahmad; Selina Schulze Spuentrup |
| Abstract: | We examine the effects of introducing prompted choice on organ donation behavior. Applying a generalized difference-in-differences design, we take advantage of the gradual roll-out of a policy in Italy that integrated the question of organ donation preference into the process of identity card renewal. Our findings show that municipalities prompting the question saw a significant increase in consent registrations, although individuals retained the option to abstain from making a choice. We also provide novel evidence that regions with higher levels of registered consent have higher cadaveric organ donation rates. |
| Keywords: | organ donation, organ donor registry, prompted choice, health policy |
| JEL: | I18 D70 |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:mag:wpaper:26010 |
| By: | Eiji YAMAMURA; Yasuyuki TODO |
| Abstract: | This study examines vote switching between Japan’s July 2025 House of Councillors and February 2026 House of Representatives elections. The Liberal Democratic Party (LDP) suffered a major defeat in 2025, then achieved a landslide victory in 2026 under Prime Minister Sanae Takaichi, who adopted a moderate but firmly immigration-restrictive platform. Based on a survey that collected 19, 945 responses, we analyzed a sub-sample of 14, 431 valid respondents using multinomial logit and Heckman selection probit models to examine party choice and vote switching. Major findings are as follows: (1) opposition to Trump-style tariffs is universal across parties, while support for immigration restriction divides voters sharply. (2) voters who switched to the LDP distrusted unverified foreigners but accepted workplace-integrated ones. (3) risk-averse voters who had supported right-wing opposition parties were especially likely to switch to the LDP. However, it should be noted that the estimation results may be biased, as the study does not account for views on topics such as the Constitution or nuclear power. |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:eti:dpaper:26044 |
| By: | Crispin Cooper (Cardiff University (Computer Science)); Ana Fredrich (Cardiff University (Computer Science)); Tommaso Reggiani (Cardiff University (Business); Masaryk University, Faculty of Economics and Administration, Brno, Czech Republic); Wouter Poortinga (Cardiff University (Architecture - Psychology)) |
| Abstract: | How should well-being be prioritised in society, and what trade-offs are people willing to make between fairness and personal well-being? We investigate these questions using a stated preference experiment with a nationally quasi-representative UK sample (n = 300), in which participants evaluated life satisfaction outcomes for both themselves and others under conditions of uncertainty. Individual-level utility functions were estimated using an Expected Utility Maximisation (EUM) framework and tested for sensitivity to the overweighting of small probabilities, as characterised by Cumulative Prospect Theory (CPT). A majority of participants displayed concave (risk-averse) utility curves and showed stronger aversion to inequality in societal life satisfaction outcomes than to personal risk. These preferences were unrelated to political alignment, suggesting a shared normative stance on fairness in well-being that cuts across ideological boundaries. The results challenge use of average life satisfaction as a policy metric and support the development of nonlinear utility-based alternatives that more accurately reflect collective human values. Implications for public policy and well-being measurement are discussed. |
| Keywords: | Subjective well-being; Experimental method; Inequality aversion; Expected utility; Prospect theory; Social welfare; Fairness trade-offs |
| JEL: | C91 D63 D81 |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:mub:wpaper:2026-04 |
| By: | Eleftherios Filippiadis (Department of Economics, University of Macedonia, Greece) |
| Abstract: | This paper studies how the distribution of preference intensity affects product survival. Consumers may have the same average valuation of a product attribute, yet differ sharply in how concentrated that valuation is across the population. I show that this distinction matters for market selection. In a differentiated-product economy with fixed operating costs, a product survives only if it attracts enough revenue to cover its fixed cost. When the revenue contribution of consumers is convex in preference intensity, concentrating a fixed aggregate valuation among fewer high-intensity consumers raises the revenue of high-attribute products. Thus, small groups of strongly attached consumers can sustain varieties that would fail under a more diffuse distribution of moderate preferences. In a ranked-attribute benchmark, this condition has a simple interpretation: the product benefits from concentration when it is sufficiently distant from the share-weighted center of the active product range. The paper also separates private survival from welfare and aggregate impact. Applications to green products and privacy-oriented digital services show that cleaner or more privacy-protective varieties improve aggregate outcomes only when they sufficiently displace dirtier or more data-intensive alternatives. |
| Keywords: | preference concentration; product survival; behavioral heterogeneity; differentiated products; green preferences; privacy preferences. |
| JEL: | D11 D43 L11 L13 Q56 |
| Date: | 2026–09 |
| URL: | https://d.repec.org/n?u=RePEc:mcd:mcddps:2026_09 |
| By: | Myeongju Kim (Yonsei University); Eunseong Ma (Yonsei University) |
| Abstract: | This paper studies how the macroeconomic effects of tax cuts depend on occupational targeting—toward entrepreneurs versus wageworkers. Using a new state-level panel of occupation specific federal tax shocks for the United States from 1981 to 2017, we find that entrepreneur targeted tax cuts generate substantially larger increases in output, consumption, and employment than revenue-equivalent worker-targeted cuts. These effects coincide with increases in both entrepreneurship and wage employment, pointing to business formation and firm expansion as key transmission channels. An incomplete-markets model with occupational choice attributes these findings to earnings-based borrowing constraints and demand-driven amplification that jointly produce large entrepreneur multipliers. |
| Keywords: | Tax policy, Entrepreneurship, Earnings-based constraints, Occupational choice |
| JEL: | E62 H25 J23 |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:yon:wpaper:2026rwp-291 |
| By: | Xavier Mateos-Planas (Queen Mary University of London, Centre for Macroeconomics); Sean McCrary (Ohio State University); Jose-Victor Rios-Rull (University of Pennsylvania, University College London, CAERP, CEPR, NBER); Adrien Wicht (University of Basel) |
| Abstract: | We characterize the equilibrium of the standard sovereign default model with long-term, non-contingent debt. We show existence of the Markov equilibrium and uniqueness of equilibria that are the limit of finite economies. In general, the price and policy functions exhibit jumps and kinks; a suitable choice of arbitrarily small noise yields price and policy functions that are differentiable everywhere, which allows us to characterize the equilibrium using only the agents’ decision rules by means of a set of functional equations. We further describe the equilibrium objects via an Euler equation with derivatives on future actions—a Generalized Euler Equation (GEE) that disentangles the effects of default from those of dilution. The GEE yields computational strategies that search for continuous policy functions. A sufficient scale of the noise ensures concavity and a unique solution of the GEE. Applied to a calibrated model following Chatterjee and Eyigungor (2012), the GEE combined with the endogenous grid method delivers residuals orders of magnitude smaller than standard value function iteration, at roughly an order of magnitude lower computational cost. |
| Keywords: | Long-term debt, Sovereign default, Generalized Euler Equation, Computational methods |
| JEL: | F34 E44 C63 G12 |
| Date: | 2026–01–06 |
| URL: | https://d.repec.org/n?u=RePEc:pen:papers:26-009 |
| By: | OECD |
| Abstract: | Digital markets have profoundly transformed the way consumers interact with businesses, offering new opportunities for innovative goods and services, greater choice, and enhanced convenience. These evolving dynamics create new challenges for both competition and consumer protection authorities, as practices that impact competition may also have an effect on consumer autonomy and choice, privacy, as well as trust, and vice versa. Traditional analytical frameworks based on price, output, information and transparency often fail to capture the full competition and consumer implications of conduct in digital environments. This note examines areas where the two policy areas converge, where gaps remain and how authorities can work together to address challenges arising from digitalisation. |
| JEL: | D12 D18 K21 L13 L40 L41 |
| Date: | 2026–05–28 |
| URL: | https://d.repec.org/n?u=RePEc:oec:dafaac:332-en |
| By: | Li-Hsien Sun; Zong-Yuan Huang; Yi-Ling Huang; Chi-Yang Chiu; Ning Ning |
| Abstract: | We study offline change-point estimation for time series data exhibiting nonlinear serial dependence. To address this problem, we propose a copula-based Markov chain model with Weibull marginal distributions, which is suitable for modeling nonnegative data such as event times and volatility measures. Nonlinear dependence is incorporated through the Clayton and Joe copulas, allowing the model to capture asymmetric lower-tail and upper-tail dependence structures, respectively. We derive the corresponding likelihood function and estimate the change point and model parameters using maximum likelihood estimation implemented through the Newton--Raphson algorithm. Confidence intervals are constructed via a parametric bootstrap Monte Carlo procedure. Extensive numerical studies are conducted to evaluate the finite-sample performance and robustness of the proposed method under different dependence structures and copula misspecification scenarios. The results demonstrate that the proposed estimators perform well in terms of RMSE and relative error, particularly for the estimation of the change point. An empirical application to the VIX index during the COVID-19 pandemic further illustrates the practical usefulness of the proposed approach in detecting structural changes in both the marginal distributions and serial dependence structure. |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2605.29541 |