Documents de travail
We show that least squares cross-validation (CV) methods share a common structure which has an explicit asymptotic solution, when the chosen kernel is asymptotically separable in bandwidth and data. For density estimation with a multivariate Student t(ν) kernel, the CV criterion becomes asymptotically equivalent to a polynomial of only three terms. Our bandwidth formulae are simple and non-iterative (leading to very fast computations), their integrated squared-error dominates traditional CV implementations, they alleviate the notorious sample variability of CV, and overcome its breakdown in the case of repeated observations. We illustrate with univariate and bivariate applications, of density estimation and nonparametric regressions, to a large dataset of Michigan State University academic wages and experience.
This paper is essentially based on the assumption that policies supporting investment in intermittent renewable technologies cannot be contingent on meteorological events causing this intermittence. This decision was taken by most policymakers to avoid overly complex policy prescriptions. But in doing so, the first-best energy mix may be out of reach. We compare, in a unified second-best setting, the feed-in tariff, renewable premiums and tradable green certificates policy. We consider a "two-period, S-state" model. The S states reflect intermittency. Production decisions for renewable electricity are taken prior to the resolution of the uncertainty while the fossil-fuel sector adjusts its decision in each state. Retailers buy electricity on a state-dependent wholesale market which they deliver to consumers according to a fixed-tariff or a real-time-pricing contract. All these elements matter in the efficiency assessment of these policies.
This paper first provides empirical evidence that labour market outcomes for the less educated workers, who also tend to be poorer, are substantially more volatile than those for the well-educated, who tend to be richer. We estimate job finding rates and separation rates by educational attainment for several European countries and find that job finding rates are smaller and separation rates larger at lower educational attainment levels. At cyclical frequencies, fluctuations of the job finding rate explain up to 80% of unemployment fluctuations for the less educated. We then construct a stylised HANK model augmented with search and matching and ex-ante heterogeneity in terms of educational attainment. We show that monetary policy has stronger effects when the job market for the less educated and, hence, poorer workers is more volatile. The reason is that these workers have the most procyclical income coupled with the highest marginal propensity to consume. An expansionary monetary policy shock that increases labour demand disproportionally affects the labour market segment for the less educated, causing a strong increase in consumption. This further amplifies labour demand and increases the labour income of the poor even more, amplifying the initial effect. The same mechanism carries over to forward guidance.
This paper computes lifetime earnings (LTE) in France for the 1967 to 1987 entry cohorts and compares our results with the US. Median LTE in France increased moderately for both genders, in contrast to the US where men's LTE declined and women's rose sharply. We also examine some of the factors driving the dynamics of LTE in France. We find that education plays a key role in shaping LTE across cohorts, place of birth has a large influence on lifetime earnings, and differences in working time explain a larger share of the gender gap for younger than for older cohorts.
The Syrian refugee crisis is one of the significant humanitarian challenges of the 21st century, and Turkey is among the countries significantly impacted. This study analyzes the impact of the approximately 3.65 million Syrian refugees residing in Turkey on economic development proxied by GDP per capita. Since Turkish provinces faced distinctive rises in refugee numbers after the Syrian Civil War, I exploit the differences in the proportion of refugees across different Turkish provinces to estimate refugees' impact on economic development using a difference-indifferences methodology. To address the potential selection bias arising from the refugees' settlement patterns, I employ a two-stage least squares (2SLS) method. Results offer suggestive evidence of a positive medium-term effect and a negative long-term effect of the arrival of refugees on economic development, while the short-term effect is unclear. However, none of the impacts are statistically significant.
The Balassa-Samuelson effect is still an important phenomenon in the theory of economic development, as Balassa states, "As economic development is accompanied by greater inter-country differences in the productivity of tradable goods, differences in wages and service prices increase, and correspondingly so do differences in purchasing power parity and exchange rates." To the best of our knowledge, the Balassa-Samuelson effect has not been formally examined in the framework of optimal growth theory. By embedding the Balassa-Samuelson’s original model in an optimal growth model setting, we investigate the validity of the Balassa-Samuelson effect in such a case and show that the Balassa-Samuelson effect follows from one of the properties of the optimal steady state.
In this paper, I introduce a novel methodology to conduct surveys. The priced survey methodology (PSM). Like standard surveys, priced surveys are easy to implement, and measure social preferences on numerical scales. The PSM's design draws inspiration from consumption choice experiments, as respondents fill out the same survey several times under different choice sets. I extend Afriat's theorem and show that the Generalized Axiom of Revealed Preferences is necessary and sufficient for the existence of a concave, continuous, and single-peaked utility function rationalizing answers to the PSM. I apply the PSM to a sample of online participants and show that most respondents are rational when answering the PSM. I estimate respondents' single-peaked utility functions and draw several implications on their social preferences.
The Balassa-Samuelson effect ("BS effect") has attracted attention as a theory to explain the stagnation of the Japanese economy over the past 30 years. In particular, it has been used to explain the long-term depreciation of the real effective exchange rate since 1995. Furthermore, macroeconomic data show that the BS effect explains well Japan's long-term economic stagnation. However, the BS effect was originally derived theoretically for small open economies, not for large economies like Japan. In other words, the BS effect cannot be theoretically applied to large economies. This is a serious problem in applying the BS effect empirically. In this paper, we embed Balassa-Samuelson's original argument into the optimal growth theory framework. That is, we set up an optimal growth problem for large countries. It is then shown that there exists a stable optimal steady state and that the BS effect is more directly valid in that optimal steady state. In other words, as a long-run property, the BS effect is applicable to large as well as small countries, although, contrary to the small open economy case, it does not depend on the capital shares of the two sectors.
To what extent protectionism affects growth and (de)stabilizes the economies? Since 2018, some countries have resorted to protectionist measures as the United States. Although the impacts of protectionism on growth have been widely explored without reaching a consensus, few has been said on its impacts on macroeconomic stability. The present paper attempts to gauge more precisely its implications using a Barro-type (1990) endogenous growth model with public debt and credit constraint where tariffs are a proxy of protectionism. Our main result is to show that when the debt level is high, and the share of foreign goods in total consumption is large enough, increasing tariffs may have a dramatic destabilizing effect generating some expectation coordination failure between multiple equilibria and the possible existence of large self-fulfilling fluctuations. We also exhibit some trade-off between tariffs and growth as tariffs are beneficial only to the low growth equilibrium which may only appear in the globally indeterminate case. We also propose some numerical illustrations confirming the destabilizing impact of tariffs in the case of the US economy. We finally propose an Event Study analysis to confront our results. While our effects appear short lasting, two quarters, we show that the implementation of protectionism destabilizes the US economy in the short run.
When can exogenous changes in beliefs generate endogenous fluctuations in rational expectation models? We analyze this question in the canonical one-sector and two-sector models of the business cycle with increasing returns to scale. A key feature of our analysis is that we express the uniqueness/multiplicity condition of equilibirum paths in terms of restrictions on five critical and economically interpretable parameters: the Frisch elasticities of the labor supply curve with respect to the real wage and to the marginal utility of wealth, the intertemporal elasticity of substitution in consumption, the elasticity of substitution between capital and labor, and the degree of increasing returns to scale. We obtain two clear-cut conclusions: belief-driven fluctuations cannot exist in the one-sector version of the model for empirically consistent values for these five parameters. By contrast, belief-driven fluctuations are a robust property of the twosector version of the model-with differentiated consumption and investment goods-, as they now emerge for a wide range of parameter values consistent with available empirical estimates. The key ingredients explaining these different outcomes are factor reallocation between sectors and the implied variations in the relative price of investment, affecting the expected return on capital accumulation.
The Malthusian trap is a well recognized source of stagnation in per capita income prior to industrialization. However, previous studies have found mixed evidence about its exact strength. This article contributes to this ongoing debate, by estimating the speed of convergence for a wide range of economies and a large part of the Malthusian era. I build a simple Malthusian growth model and derive the speed of convergence to the steady state. A calibration exercise for the English Malthusian economy reveals a relatively weak Malthusian trap, or weak homeostasis, with a half-life of 112 years. I then use β-convergence regressions and historical panel data on per capita income and population to empirically estimate the speed of convergence for a large set of countries. I find consistent evidence of weak homeostasis, with the mode of half-lives around 120 years. The weak homeostasis pattern is stable from the 11th to the 18th century. However, I highlight significant differences in the strength of the Malthusian trap, with some economies converging significantly faster or slower than others.
Ob jectives: To analyse how general practitioners (GPs) respond to insucient GP supply in their practice area in terms of quantity and quality of care, and how this response can be mediated by enrolment in integrated primary care teams (multi-professional group practices (MGP)).
Methods: We used three representative cross-sectional surveys (2019-2020) of 1,209 French GPs. Using structural equations, we assumed that low GP density inuences GPs' work-related stress (mediator 1) as well as their use of e-health tools (mediator 2) and ultimately quantity and quality of care. Quantity (respectively quality) of care were approximated by demand absorption capacities (respectively frequencies of vaccine recommendations). We estimated an additional specication where enrolment in an MGP was a mediator between GP density and the two mediators dened above.
Results: GP density was signicantly and positively associated with work-related stress, which was consecutively associated with deteriorated demand absorption capacity. Higher use of e-health tools was associated with greater involvement in vaccine recommendations. Lastly, GPs in MGP tend to use more e-health tools than those practicing outside MGP, with a favourable eect on quality of care.
Discussion: This study demonstrates that a lower level of work-related stress is the key mediator in handling patients' requests. Correcting for the self-selection into MGP, we amend some unstable results contained in the literature: there is no signicant mediation eect of enrolment in integrated primary care teams on the quantity of care, but rather an eect on the quality of care. Although probably disappointing for the quantity of care provided, our results pinpoint a novel added value of enrolment in an integrated practice as a response to decreasing GP density.
This paper contributes to the literature interested in the new factors that may determine fertility behaviors. Many studies underlay that environmental concerns have a direct effect on households' fertility decisions. We present a dynamic model that explicitly examines this interplay, considering whether the number of children and environmental concerns may be complementary or substitutable. Interesting results occur when environmental concerns and the number of children are substitutable. At a stable steady state, a stronger effect of environmental concerns on household's preferences reduces the number of children, as also stressed by a recent literature. The dynamics can be described by an inversely Ushaped relationship between fertility and environmental indicators reflecting the impact of economic production, such as the carbon intensity, as we illustrate using data on US States. The dynamics also explain that regions with lower carbon intensity are those with lower fertility.
Aims: we propose a sociotechnical taxonomy for the analysis of socioeconomic disruptions caused by technological innovations. Methodology: a transdisciplinary principled approach is used to build the taxonomy through categorization and characterization of technologies using concepts and definitions originating from cybernetics, occupational science, and economics. The sociotechnical taxonomy is then used, with the help of logical propositions, to connect the characteristics of different categories of technologies to their socioeconomic effects, for example their externalities. Results: we offer concrete illustrations of concepts and uses, and an Industry 5.0 case study as an application of the taxonomy. We suggest that the taxonomy can inform the analysis of opportunities and risks related to technological disruptions, specially of those that result from the rise of cognitive machines.
In this paper, we examine rebalancing strategies for long-term institutional investors. Specifically, we test the difference in risk-adjusted performances between stock-bond portfolios based on buy-and-hold, periodic and threshold rebalancing strategies. Using the Norwegian Sovereign Wealth Fund (SWF) as a benchmark and an econometric approach based on a bootstrap test of Sharpe ratios difference, we show that the optimal rebalancing differs across economic and financial cycles. Furthermore, we find that the optimal strategy is periodic rebalancing except during recessions and crises when the buy-and-hold approach is best, thus calling into question the hypothesis of the countercyclical behavior of SWFs. Our results are robust to alternative performance measures, asset allocations, investment horizons, rebalancing rule, nonnormal and non-iid returns, transaction costs and time sampling. Finally, our findings promote the consideration of macroprudential rules to improve the Santiago Principles and a specific monitoring framework targeted at SWFs.
Higher uncertainty about trade policy has recessionary effects in U.S. states. First, this paper builds a novel empirical measure of regional trade policy uncertainty, based on the volatility of national import tariffs at the sectoral level and the sectoral composition of imports in U.S. states. We show that a state which is more exposed to an unanticipated increase in tariff volatility suffers from a larger drop in real output and employment, relative to the average U.S. state. We then build a regional open-economy model and we argue that the transmission channels of uncertainty shocks, in particular the precautionary-pricing channel, are magnified in regions that feature the highest import share and a strongest export intensity. Furthermore, we show that an expansionary monetary policy may amplify the regional divergence since it worsens the recession in the most-exposed region to trade policy uncertainty.
Survey data are known for under-reporting rich households while providing large information on contextual variables. Tax data provide a better representation of top incomes at the expense of lacking any contextual variables. So the literature has developed several methods to combine the two sources of information. For Pareto imputation, the question is how to chose the Pareto model for the right tail of the income distribution. The Pareto I model has the advantage of simplicity. But Jenkins (2017) promoted the use of the Pareto II for its nicer properties, reviewing three different approaches to correct for missing top incomes. In this paper, we propose a Bayesian approach to combine tax and survey data, using a Pareto II tail. We build on the extreme value literature to develop a compound model where the lower part of the income distribution is approximated with a Bernstein polynomial truncated density estimate while the upper part is represented by a Pareto II. This provides a way to estimate the threshold where to start the Pareto II. Then WID tax data are used to build up a prior information for the Pareto coefficient in the form of a gamma prior density to be combined with the likelihood function. We apply the methodology to the EU-SILC data set to decompose the Gini index. We finally analyse the impact of top income correction on the Growth Incidence Curve between 2008 and 2018 for a group of 23 European countries.
Revolutions are often perceived as the key event triggering the fall of an autocratic regime. They are believed to be driven by the people with the purpose of establishing a democratic regime for the people. However, the historical record does not agree with this picture: revolutions are rare, elite-driven, and often non-democratising. We first develop a new set of stylised facts summarising and deepening the latter features. Second, to explain these facts, we develop a theory of elite-driven non-democratising institutional changes triggered by popular uprisings. Our model includes four key ingredients: (i) a minority/majority split in the population; (ii) the persistence of fiscal particularism post-revolution; (iii) the presence of windfall resources; (iv) a distinction between labour income and resource windfalls as well as endogeneity of the labour supply. We show that revolutions are initiated by the elite and only when fractionalisation is moderate. Resource windfalls and labour market repression can also play a role in triggering this 'alliance' between the majority and the elite. If a revolution happens, redistribution in the subsequent regime still favours the elite, although the masses are better off.
While the educational expansion of the 20 th century promoted social mobility overall, the top of the social hierarchy may have remained privileged. This paper examines the evolution of intergenerational mobility in admissions to the French elite colleges-the Grandes Écoles (GE)-over more than a century. Admission to these institutions is subject to partially anonymous competitive examinations, and their degrees are the ticket to top positions in the public and private sectors. In the growing literature measuring intergenerational mobility through surnames, I design a novel method and apply it to a self-collected dataset on all 285,286 graduates from ten of the most prestigious Grandes Écoles between 1886 and 2015. Principally, I find that children of male GE graduates were highly over-represented in the top colleges throughout the 20 th century. Importantly, unlike previous studies exploiting fathers' socio-professional categories, I find a stable low level of intergenerational mobility for all cohorts born since 1916: chances of GE admission for children of GE graduates were approximately 80 times higher than for the rest of the population.
We consider public goods games played on a potentially non-symmetric network and provide comparative statics results on individual and aggregate contributions, as well as on the effect of transfers between players. We show that, contrary to the case of the complete and symmetric network, a positive shock on a player can have adverse consequences. First, it could actually decrease this player's contribution, unless the interaction matrix is a P-matrix. Second, a positive shock on a contributing player increases aggregate contributions, but a positive shock on a non-contributing player will decrease aggregate contributions, even if the player who benefited from the positive shock increases his own contribution. In each case we provide simple conditions to determine whether a positive shock will have positive or negative consequences on contributions, by looking at the unconstrained solution of an alternative, associated game. The sign of the coordinates of this solution determines the effect of a shock. With this in hand, we further show that the aggregate neutrality result of Andreoni [1990] regarding transfers between players generally does not hold on non-symmetric networks and provide conditions for it to hold. Finally, as an application of previous results, we consider introducing agents that follow Kantian moral principles and show that, depending on their position in the network, the presence of Kantian agents can, counter-intuitively, lead to a decrease in aggregate contributions.
Mexican cities along the US-Mexico border, especially Cd. Juarez became notorious due to high femicide rates supposedly associated with maquiladora industries and the NAFTA. Nonetheless, statistical evaluation of data from 1990 to 2012 shows that their rates are consistent with other Mexican cities’ rates and tend to fall with increased employment opportunities in maquiladoras. Femicide rates in Cd. Juarez are in most years like rates in Cd. Chihuahua and Ensenada and, as a share of overall homicide rates, are lower than in most cities evaluated. These results challenge conventional wisdom and most of the literature on the subject.
Several representativeness issues affect the available data sources in studying populations' income distributions. High-income under-reporting and non-response issues have been evidenced to be particularly significant in the literature, due to their consequence in underestimating income growth and inequality. This paper bridges several past parametric modelling attempts to account for high-income data issues in making parametric inference on income distributions at the population level. A unified parametric framework integrating parametric income distribution models and popular data replacing and reweighting corrections is developped. To exploit this framework for empirical analysis, an Approximate Bayesian Computation approach is developped. This approach updates prior beliefs on the population income distribution and the high-income data issues pressumably affecting the available data by attempting to reproduce the observed income distribution under simulations from the parametric model. Applications on simulated and EU-SILC data illustrate the performance of the approach in studying population-level mean incomes and inequality from data potentially affected by these high-income issues.
Recent empirical analysis of income distributions are often limited by the exclusive availability of data in a grouped format. This data format is made particularly restrictive by a lack of information on the underlying grouping mechanism and sampling variability of the grouped-data statistics it contains. These restrictions often result in the unavailability of an analytical parametric likelihood function exploiting all information available in the grouped data. Building on recent methods for inference on parametric income distributions for this type of data, this paper explores a new Approximate Bayesian Computation (ABC) approach. ABC overcomes the restrictions posed by grouped data for Bayesian inference through a non-parametric approximation of the likelihood function exploiting simulated data from the income distribution model. Empirical applications of the proposed ABC method in both simulated and World Bank's PovCalNet data illustrate the performance and suitability of the method for the typical formats of grouped data on incomes.
As physics provides the equations of motion of a body, this paper formulates, for the first time, at the conceptual and mathematical levels, the inequations of motion of an individual seeking to meet his needs and quasi needs in an adaptive (not myopic) way. Successful (failed) dynamics perform a succession of moves, which are, at once, satisficing and worthwhile (free from too many sacrifices), or not. They approach or reach desires (fall in traps). They balance the desired speed of approach to a desired end (a distal promotion goal) with the size of the required immediate sacrifices to go fast (a proximal prevention goal). Therefore, each period, need/quasi need satisfaction success requires enough self control to be able to make, in the long run, sufficient progress in need/quasi need satisfaction without enduring, in the short run, too big sacrifices. A simple example (lose or gain weight) shows that the size of successful moves must be not too small and not too long. A second paper will solve this problem, using variational principles and inexact optimizing algorithms in mathematics. This strong multidisciplinary perspective refers to a recent mathematical model to psychology: the variational rationality theory of human life stay and change dynamics.
We investigate the role of ENSO climate patterns on global economic conditions. The estimated model is based on a rich and novel monthly dataset for 20 economies, capturing 80.2% of global output (based on 2021 IMF data) over the period 1999:01 to 2022:03. The empirical evidence from an estimated global vector autoregression with local projections (GFAVLP) model links an El Niño (EN) shock with higher output and inflation, corresponding with lower global economic policy uncertainty (GEPU). While a shock to the world oil and food price is inflationary, a food price shock leads to elevated GEPU, more so during a LN shock. A main finding is that an increase of the food price can be a source of global vulnerability. The findings indicate that the weather shock impact on global economic conditions is dependent on the climate state. Our result undermines existing studies connecting climate change and economic damage via statistical approach.
This paper provides a general and formalized theory of self-regulation success and failures as an application of the recent Variational rationality approach of stay and change human dynamics (Soubeyran, 2009, 2010, 2021.a,b,c,d). For concreteness purposes, it starts with an example in psychology: how to gain or to loose weight ? It ends with a general, conceptual, dynamical and computable formulation of self-regulation and goal pursuit in the context of variational principles and adaptive optimizing algorithms in mathematics.
We develop a model of incomplete employment contracts such that employees have some discretion over effort, which depends on their work morale. Nominal wage cuts have a strong negative effect on morale, while employee involvement in workplace decision-making tends to increase morale. We derive predictions on how these two mechanisms affect the decisions of firms to cut nominal wages. Using matched employer-employee and manager survey data from Great Britain, we find support for our model: nominal wage cuts are only half as likely when managers think that employees have some discretion over how they perform their work, but this reduced likelihood recovers partially when employees are involved in the decision-making process at their workplace.