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on Macroeconomics |
| By: | Asger Lau Andersen (University of Copenhagen); Niels Johannesen (Saïd Business School, Oxford University); Jens Brøndum Petersen (University of Copenhagen); Sonja Settele (University of Cologne, ECONtribute, Max Planck Institute for Behavioral Economics); Johannes Wohlfart (University of Cologne, ECONtribute, Max Planck Institute for Behavioral Economics) |
| Abstract: | How do households respond when deposit rates drop below zero? Using administrative micro data and exploiting cross-bank variation in interest rate policies, we study a major episode of negative deposit rates in Denmark affecting two thirds of household deposits. We find that households strongly reduced deposit balances when exposed to negative deposit rates, allocating funds to stock portfolios and consumption. In a large-scale survey, we document important roles for loss aversion, perceived unfairness, intertemporal substitution and return considerations in driving these responses. Our findings suggest that monetary policy can have strong consumption effects in negative territory. |
| Keywords: | Negative interest rates, households, consumption, monetary policy |
| JEL: | D14 D83 D84 D91 E21 E43 E52 E71 |
| Date: | 2026–06 |
| URL: | https://d.repec.org/n?u=RePEc:ajk:ajkdps:418 |
| By: | Jan Lukas Schäfer (CEMFI, Centro de Estudios Monetarios y Financieros) |
| Abstract: | Previous studies have shown that banks avoid passing negative monetary policy rates through to depositors, implying losses in deposit taking that erode equity and eventually have a negative impact on the lending of capital constrained banks. This paper shows that unconstrained banks respond differently, increasing loan supply even more with a deposit zero lower bound (D-ZLB) than without it. As a result, rate cuts below zero can be more stimulative than in positive territory, provided enough banks are unconstrained. A calibrated dynamic model finds this effect substantial, increasing aggregate loan supply by about 9% despite equity erosion pressures. |
| Keywords: | Negative interest rates; bank lending; deposit zero lower bound; financial stability. |
| JEL: | E43 E52 G21 |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:cmf:wpaper:wp2026_2606 |
| By: | Valverde-Ambriz, Ismael D. |
| Abstract: | We develop a state-space framework that jointly estimates central bank credibility as a scalar latent variable and the associated time-varying monetary policy reaction function. The Kalman filter extracts an unobservable credibility index from observed inflation expectations, while Recursive Least Squares continuously updates the reaction function coefficients using the Kalman innovations sequence, ensuring that parameter estimation operates on long-run trend components rather than transitory fluctuations. Under standard regularity conditions, we establish consistency of the credibility estimator and show that the reaction function coefficients attain the Cramer-Rao bound when the innovation variance is constant; a GLS variant achieves efficiency in the heteroskedastic case. Applying the framework to Banco de Mexico over 2002-2024, we identify four distinct credibility regimes: a consolidation phase following the adoption of inflation targeting (2002-2008), a transitory shock during the global financial crisis (2008-2009), a sustained high-credibility equilibrium (2010-2020), and a stress episode associated with post-pandemic inflation (2021-2023) followed by partial recovery. The time-varying reaction coefficients reveal that Banco de Mexico's responsiveness to the inflation gap is itself a function of its credibility state: stronger anchoring permits a more measured policy response, while credibility deterioration triggers sharper, front-loaded adjustments. These findings have direct implications for the optimal design of monetary policy communication in emerging markets and for the broader debate on whether central bank credibility generates real persistent effects beyond its role in expectation coordination. |
| Keywords: | Central bank credibility, Kalman filter, recursive least squares, time-varying parameters, inflation targeting, emerging markets, Banco de Mexico |
| JEL: | C32 C33 E31 E52 E58 |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:129329 |
| By: | Sung Je Byun; Johnathan Loudis; Lawrence D.W. Schmidt |
| Abstract: | We construct a Broad Market Factor (BMF), which is a proxy for the value-weighted equity return on all firms in the US economy (public and private). The BMF differs from the standard Value-weighted Market Factor (VMF), which reflects the value-weighted equity return on public firms. We define the difference between the VMF and the BMF to be the Idiosyncratic Financial Factor (IFF). The IFF carries no risk premium and is uncorrelated with all macroeconomic proxies for investor marginal utility we consider. CAPM betas and, consequently, discount rates are underestimated when measured with respect to the VMF compared to the BMF for most portfolios. Size factors become redundant and the size anomaly is resolved when the VMF is replaced by the BMF in standard factor models. The intertemporal risk-return relation is substantially stronger when one replaces the VMF with the BMF. The unifying explanation for these results is that the IFF adds unpriced risk to the VMF, distorting both cross-sectional and time-series estimates of exposure to priced market risk. |
| JEL: | C15 C58 G12 G17 |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35243 |
| By: | Johannes Wachs; Xiangnan Feng; Simone Daniotti; Frank Neffke |
| Abstract: | With the rise of new industries, often new jobs emerge. Evolutionary Economic Geography and in particular Industry Life Cycle perspectives predict that these activities first emerge in a limited number of cities to then diffuse to other locations as job descriptions become more standardized. Here, we focus on a particularly important new industry: software development, an activity that is economically important, quickly changing, and has a pronounced spatial concentration in a small number of global IT hubs. We use an online database of over 60 million questions and answers about problems in software development that yields a longitudinal dataset of 237 software skills. By geo-locating 3 million posting users at regular intervals, we link these skills to cities worldwide. We find that, in spite of its digital nature, the software industry exhibits similar spatial regularities as previously observed in more traditional sectors. First, cities diversify into skills that are related to their existing ones. Second, new skills first emerge in cities with large and diversified software sectors, and later diffuse -- mostly unhindered by geographical distance -- to smaller cities specialized in closely related skills. We find suggestive but limited support for a windows of locational opportunity account: although even brand-new skills still emerge first in cities with strong prior specialization in related skills, concentrations of related activities impact less the emergence of new skills than the diffusion of existing ones. |
| Date: | 2026–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2606.09463 |
| By: | Dana Golden; Aruna Balasubramanian; Niranjan Balasubramanian |
| Abstract: | Data centers now account for 4.4% of United States electricity demand, yet the grid-level effectiveness of the renewable energy certificates (RECs) and power purchase agreements (PPAs) hyperscalers use to claim carbon neutrality remains unclear. We develop a game-theoretic model in which a data center operator chooses among RECs, PPAs, and behind-the-meter colocation while generators make entry decisions under endogenous financing costs. The model identifies a timing wedge -- the mismatch between consumption and credited renewable generation -- as a central mechanism through which AI demand degrades reliability, raises prices, and increases emissions even when RECs cover 100% of annual consumption. Colocation with storage addresses this wedge directly and induces the greatest renewable entry by eliminating generator revenue risk. We test these predictions by exploiting the staggered release of large language models as a natural experiment, using difference-in-differences on a novel dataset linking AI activity to local grid outcomes. AI demand significantly increases fossil generation, wholesale prices (up to 25% in treated PJM zones), and outage frequency (0.5--1 additional outages per year) near data centers, with impacts scaling in model size. Data centers with on-site generation exhibit a sign reversal in power-quality effects, consistent with the model's prediction that behind-the-meter capacity absorbs demand spikes. Counterfactual analyses show that edge inference, spatial reallocation, and colocated storage each substantially mitigate grid impacts, while REC-only strategies do not. Together, our results demonstrate that the externalities of AI to the grid are tightly coupled to procurement design and the spatial organization of data center infrastructure. |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2606.00811 |
| By: | Daniel Marcel te Kaat; Alexander Raabe |
| Abstract: | How do international investors adjust portfolios in response to biodiversity risk? Using monthly data on investment fund portfolios, we show that the 2021 Kunming Declaration led fund managers to reallocate portfolios from high-biodiversity risk countries to less risky ones, while ultimate fund investors remained unresponsive. Fund managers reduced exposures to extremely high biodiversity risk without seizing low biodiversity risk as an opportunity for profit, characterizing biodiversity as downside risk factor. Investment funds drive cross-country spillovers as the reallocation triggers significant capital flows beneï¬ ting countries in the same geographic region, but outside of a fund's hitherto established portfolio. Using a novel measure of legal action to protect nature, we demonstrate that countries adopting more legal acts are partially shielded from funds reducing their exposure to high-biodiversity risk countries. |
| Keywords: | biodiversity, risk, portfolio reallocation, cross-border capital flows, spillovers, investment fund, Kunming Declaration |
| JEL: | F3 G1 G2 Q5 |
| Date: | 2026–06 |
| URL: | https://d.repec.org/n?u=RePEc:een:camaaa:2026-41 |
| By: | Xiao Ma; Zi Wang; Xiaodong Zhu |
| Abstract: | We develop a dynamic multi-country trade model with trade-related technology diffusion and endogenous R&D to quantify the impacts of trade policies and trade wars on innovation, technology rivalry, and welfare. We estimate the model using data on trade and patent citations and validate it in the context of U.S. export controls on China. Counterfactual analysis yields three main results. First, U.S. export controls on China reduce technological progress in both countries: China experiences a sharp contraction in knowledge inflows, while the U.S. faces a decline in R&D. Second, trade-driven diffusion and endogenous innovation substantially amplify the technological and welfare gains in the U.S. and losses in other major economies from the 2025 Liberation Day tariffs. Third, U.S. optimal tariffs on China, under varying geopolitical concerns, reflect a trade-off between curbing technology diffusion to China and sustaining U.S. innovation. |
| Keywords: | Trade-related Technology Diffusion; Innovation; Endogenous Growth Model; Trade War; Optimal tariffs |
| JEL: | F12 F13 F14 O31 O33 |
| Date: | 2026–06–11 |
| URL: | https://d.repec.org/n?u=RePEc:tor:tecipa:tecipa-824 |
| By: | Kenneth R. Ahern |
| Abstract: | This paper shows that the industrial composition of a city's local economy affects its municipal borrowing costs. In a panel of 1, 177 U.S. cities from 2005 to 2022, greater sectoral concentration magnifies default risk and raises bond spreads, especially for cities dominated by industries associated with low property values. Instrumental variables exploiting national sector-employment trends and regional house-price variation support a causal interpretation. A calibrated model of city default suggests that the observed spread effect understates the gross risk created by concentration, because higher concentration can generate agglomeration benefits that reduce spreads, especially for high-property-value cities. |
| JEL: | G12 H74 R51 |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35228 |
| By: | Reichel, Felix |
| Abstract: | Drafting in the swim leg of mass-start triathlon transfers a hydrodynamic cost advantage to the bike and run, where it surfaces as a change in relative rank. I use cross-stage rank improvement as a reverse proxy for free-riding and study its determinants in a ten-year panel of athlete × event records centred on 2020, when COVID-19 response policies replaced mass starts with individually staggered starts and mechanically curtailed drafting. A compact two-stage contest model, in which drafting enters the bike–run stage as a multiplicative cost shifter, organises the predictions. Identification combines pooled OLS with athlete and event fixed effects and a sharp regression-discontinuity design at the 2019/2020 cut-off. Free-riding was substantial before 2020, fell sharply in 2020 (a local-linear RDD estimate of about −31 rank places; a local-cubic estimate of about −92), and recovered only partially afterwards. The gains are largest for weaker swimmers and deeper drafting positions, the gender gap is modest, and they rise with swim-group size at an estimated log–log elasticity of about 0.43. The 2020 disruption thus acts as a contraction of the feasible set for free-riding, and its recovery is uneven rather than broad-based. |
| Date: | 2026–06–02 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:dyrcf_v2 |
| By: | Wagner, Leandro |
| Abstract: | Liquidity is central to modern fixed-income markets, yet it is often treated too simply. Bonds are commonly described as liquid or illiquid, as though liquidity were a fixed quality built into the security itself. This book challenges that view. It argues that liquidity is not a permanent feature of a bond, but a fragile condition created by market structure, financing arrangements, collateral rules, dealer capacity, valuation practices, regulation, and investor behaviour. The Endogeneity of Liquidity Risk in Leveraged Fixed-Income Systems develops a clear theory of how liquidity is created inside the financial system and how it can disappear under stress. A bond may appear easy to sell in calm markets, financeable through repo, acceptable as collateral, and stable in daily valuation. Yet those qualities may depend on conditions that change quickly when volatility rises, funding tightens, or many investors try to exit at the same time. |
| Keywords: | Liquidity Risk Endogeneity Leveraged Finance Fixed-Income Markets Systemic Risk Market Liquidity Funding Liquidity Financial Stability Bond Markets Leverage Cycles Liquidity Spirals Asset Fire Sales Margin Constraints Financial Contagion Macroprudential Regulation Market Microstructure Credit Markets Repo Markets Risk Transmission Stress Dynamics Fragility Procyclicality Capital Markets Dealer Intermediation Liquidity Shocks |
| JEL: | D0 H3 O1 |
| Date: | 2026–03–03 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:129114 |
| By: | Yong Zhang; Xinxiao Wu; Yunde Jia; Che Sun |
| Abstract: | Accurate stock price forecasting has consistently remained a pivotal yet challenging FinTech task that underpins quantitative trading and investment decision making. Recent efforts have been dedicated to modeling various complex relationships among stocks in the stock market toward more reliable stock price forecasting.These methods depend heavily on strong static prior assumptions by modeling either temporal dependencies within individual stocks or spatial dependencies across different stocks based on predefined structures, while the complex market dynamics that drive stock price movements remain unexplored. To alleviate this issue, we propose a novel game-theoretic modeling method that captures heterogeneous investor interactions for stock price forecasting. The core idea is to embed game-theoretic mechanisms into the heterogeneous graph structure to finely model the dynamic strategic interactions among heterogeneous investors with respect to target stocks. Additionally, temporal positional encoding is adopted to reflect the differentiated influences of each game event at different time steps within the time window on future stock price movements. Leveraging heterogeneous graph networks, we proxy the intricate dynamics of the stock market through investor games and enable real-time information propagation and node updates among all nodes. Extensive experiments conducted on two real-world benchmark dataset demonstrate that our method effectively outperforms state-of-the-art stock price forecasting methods. |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2605.23953 |
| By: | Ian Crawford; Longye Tian |
| Abstract: | We examine how the empirical content of revealed preference theory depends on the dimensionality of the choice environment. While higher-dimensional choice problems may appear more demanding, we show that revealed preference restrictions become less informative. Using Selten's Area measure, we establish that for any fixed number of observations, the empirical content of GARP converges to zero exponentially fast in the number of goods. We provide complementary proofs based on revealed preference graphs and the Afriat inequalities, and show in simulations calibrated to scanner data that the effect is quantitatively large. We also evaluate potential responses in observational and experimental settings and find that, while these can slow the rate, they do not eliminate this loss of empirical content. |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2605.29361 |
| By: | Louise Devos (Ghent University (UGent@Work, CESSMIR)); François Rycx (ULB (CEBRIG, DULBEA), UMONS (Soci&ter), UCLouvain (IRES), GLO and IZA); Thomas Senterre (ULB (CEBRIG, DULBEA), UMONS (Soci&ter)); Mélanie Volral (UMONS (Soci&ter) and ULB (CEBRIG, DULBEA)) |
| Abstract: | Using matched employer–employee data on more than 62, 000 master’s graduates, this paper examines how gender differences in wage returns to fields of study vary by migration background and how educational specialisation contributes to the gender wage gap. We estimate wage regressions and apply a decomposition approach to separate sorting across fields from differences in pay within fields. Returns vary widely, with law, economics and management, and science yielding the highest returns, and women earning less than men within all fields, especially in high-paying ones. First-generation immigrants from developing countries obtain the lowest returns regardless of field of study, while second-generation immigrants approach but do not fully match natives. Fields of study explain a substantial share of gender wage inequality among natives and second-generation immigrants, whereas among first-generation immigrants broader wage disadvantages dominate. Results further vary with the number of parents originating from developing countries and with age at arrival. |
| Keywords: | gender wage gap, first- and second-generation immigrants, field of study, employer-employee data |
| JEL: | I24 I26 J16 J31 |
| Date: | 2026–05–08 |
| URL: | https://d.repec.org/n?u=RePEc:ctl:louvir:2026009 |
| By: | Mariusz Kapuściński (Narodowy Bank Polski) |
| Abstract: | The effects of the bank levy in Poland on the broadly defined credit market (including on loan rates and volumes) appear to be well documented, with the use of the standard difference-in-differences (DID) method. However, as, for example, Borusyak et al. (2024) note, in a setting with staggered treatment (as in the case of the bank levy in Poland), and different effects of the treatment in time and between cross-sections, the method might provide biased estimates. None of the studies to date used the heterogenous DID method that addresses this drawback. In this research note I use the heterogenous DID method to estimate the consequences of the bank levy. I also discuss other methodological choices. Among other things, I find that the bank levy has lowered deposit rates, raised rates on loans for house purchases, and changed the composition and the level of bank assets. However, I find no longer-term crowding out of credit by government bond securities (while the latter did increase, the former did not increase) or effects on bank profitability. The use of a more advised method did not lead to results in stark contrast with the earlier literature applying methods for causal inference. |
| Keywords: | bank levy, difference-in-differences, panel data, financial stability |
| JEL: | C23 E43 E51 E52 G18 H26 H39 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:nbp:nbpmis:388 |
| By: | Kleifgen, Eva (Institute for Employment Research (IAB), Nuremberg); Roth, Duncan (Institute for Employment Research (IAB), Nuremberg); Stepanok, Ignat (Institute for Employment Research (IAB), Nuremberg) |
| Abstract: | The COVID-19 pandemic has caused major disruptions in international trade and has raised concerns about adverse effects on international supply chains. Using a unique establishment survey matched with administrative data from Germany, we provide novel evidence on how establishments have adjusted their supply chains in response to pandemic-induced disruptions. We find that establishments that experienced difficulties in obtaining intermediate inputs as a result of the pandemic are significantly more likely to change their network of suppliers than establishments without such problems, especially if disruptions affected imports from abroad. Establishments experiencing supply chain difficulties are more likely to replace a distant with a closer supplier. However, these adjustments in response to the pandemic appear to be temporary. |
| Keywords: | COVID-19 pandemic, establishments, supply chains, imports, Germany, intermediate inputs |
| JEL: | D22 F14 |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18669 |
| By: | Yujiao Chen |
| Abstract: | We study risk-neutral control in Markov decision processes with an absorbing catastrophic state. Even though rewards are linear and the agent has no utility curvature, probability weighting, or framing dependence, standard Bellman optimality produces three prospect-theory-like signatures: an S-shaped value-function profile (convex near catastrophe, concave in the far field), an endogenous loss-sensitivity coefficient $\lambda^*(S) > 1$, and a reflection-effect policy reversal. Across 495 configurations, the optimal policy plays safe near catastrophe in positive-drift (growth) regimes despite the risky action's higher immediate expected value, and plays risky near catastrophe in negative-drift (decline) regimes despite the safe action's lower immediate expected loss. We derive a closed-form expression for the asymptotic loss-aversion plateau $\bar{\lambda}$ that depends only on win probability $p$, payoff asymmetry $r = |\Delta_\ell/\Delta_w|$, and discount factor $\beta$, and matches numerical solutions to $R^2 = 0.999$. The mechanism does not require asymmetric payoffs. Across a sweep of $(p, \beta)$ at three asymmetry levels, the asymmetry share of $\bar{\lambda}$ above unity has median 4.6% at $r = 1.25$ and rises to 13.9% at $r = 2$, with the boundary contribution exceeding the asymmetry contribution in every cell tested. The phenomena persist under tabular Q-learning (a model-free agent reproduces $V^*$ at correlation 0.98 in growth and 1.00 in decline) and under stochastic transitions with Gaussian, heavy-tailed Student-$t_3$, and asymmetric skew-normal noise up to 50% of the step size, where the asymptotic plateau tracks the closed-form prediction within 0.41% for safe-channel noise and within 9.6% for risky-channel or both-channel noise. These results identify absorbing failure states as a sufficient structural mechanism for prospect-theory-like behavior under optimal control. |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2606.00970 |
| By: | Olle Folke; Torbjørn Hanson; Åshild A. Johnsen; Andreas Kotsadam; Johanna Rickne |
| Abstract: | We develop an information-based intervention against sexual harassment and test it in a randomized control trial across small groups of military recruits in the boot camp of the Norwegian military. The intervention seeks to bridge two knowledge gaps with implications for sexual harassment prevalence. We tell some recruits about their peers' beliefs that "telling sexualized jokes can be labeled sexual harassment" and about women soldiers' equal performance on military skill tests. This treatment gives lasting improvements in knowledge about what sexual harassment is and about women's job performance. The impact on sexual harassment prevalence is directionally negative but statistically insignificant. We discuss measurement error and use survey responses about a harassment scenario to argue that the intervention likely affected behavior. Our study provides the first field experiment to evaluate whether a prevention method against sexual harassment reduces prevalence in a work setting. We use insights from our research process to identify methodological pitfalls and provide guidance for future field experiments in this area. |
| Keywords: | Sexual harassment, Randomized controlled trial, Information provision experiment |
| JEL: | J16 C93 M54 |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:crm:wpaper:26138 |
| By: | Vasnev, Andrey; Liu, Chu-An |
| Abstract: | This paper proposes corrected forecast combinations when the original combined forecast errors are serially dependent. Motivated by the classic Bates and Granger (1969) example, we show that combined forecast errors can be strongly autocorrelated and that a simple correction – adding a fraction of the previous combined error to the next-period combined forecast – can deliver sizable improvements in forecast accuracy, often exceeding the original gains from combining. We formalize the approach within the conditional-risk framework of Gibbs and Vasnev (2024), in which the combined error decomposes into a predictable component (measurable at the forecast origin) and an innovation. We then link this correction to efficient estimation of combination weights under time-series dependence via GLS, allowing joint estimation of weights and an error-covariance structure. Using the U.S. Survey of Professional Forecasters for major macroeconomic indices across various subsamples (including pre/post-2000, GFC, and COVID), we find that a parsimonious correction of the mean forecast with a coefficient around 0.5 is a robust starting point and often yields material improvements in forecast accuracy. For optimal-weight forecasts, the correction substantially mitigates the forecast combination puzzle by turning poorly performing out-of-sample optimal-weight combinations into competitive forecasts. |
| Keywords: | Monetary policy indicators, China, forecast combination, optimal weights |
| Date: | 2026–01–21 |
| URL: | https://d.repec.org/n?u=RePEc:syb:wpbsba:2123/34743 |