AMU - AMSE
5-9 Boulevard Maurice Bourdet, CS 50498
13205 Marseille Cedex 1
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- Pintus
Pintus
Patrick Pintus
Enseignant-Chercheur
,
Aix-Marseille Université
,
Faculté d'économie et de gestion (FEG)
,
INSHS CNRS
Statut
Professeur des universités
Domaine(s) de recherche
Macroéconomie
Thèse
1997
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École des hautes études en sciences sociales
Contact
papintus[at]gmail.com
Adresse
Îlot Bernard du Bois
Publications
We provide a novel way to correct the effective reproduction number for the time-varying amount of tests, using the acceleration index (Baunez et al., 2021) as a simple measure of viral spread dynamics. Not correcting results in the reproduction number being a biased estimate of viral acceleration and we provide a formal decomposition of the resulting bias, involving the useful notions of test and infectivity intensities. When applied to French data for the COVID-19 pandemic (May 13, 2020—October 26, 2022), our decomposition shows that the reproduction number, when considered alone, characteristically underestimates the resurgence of the pandemic, compared to the acceleration index which accounts for the time-varying volume of tests. Because the acceleration index aggregates all relevant information and captures in real time the sizable time variation featured by viral circulation, it is a more parsimonious indicator to track the dynamics of an infectious disease outbreak in real time, compared to the equivalent alternative which would combine the reproduction number with the test and infectivity intensities.
The interest rate at which US firms borrow funds has two features: (i) it moves in a countercyclical fashion and (ii) it is an inverted leading indicator of real economic activity: low interest rates today forecast future booms in GDP, consumption, investment, and employment. We show that a Kiyotaki–Moore model accounts for both properties when interest-rate movements are driven, in a significant way, by self-fulfilling belief shocks that redistribute income away from lenders and to borrowers during booms. The credit-based nature of such self-fulfilling equilibria is shown to be essential: the dynamic correlation between current loanable funds rate and future aggregate economic activity depends critically on the property that the interest rate is state-contingent. Bayesian estimation of our benchmark DSGE model on US data shows that the model driven by redistribution shocks results in a better fit to the data than both standard RBC models and Kiyotaki–Moore type models with unique equilibrium.
An acceleration index is proposed as a novel indicator to track the dynamics of COVID-19 in real-time. Using data on cases and tests in France for the period between the first and second lock-downs—May 13 to October 25, 2020—our acceleration index shows that the pandemic resurgence can be dated to begin around July 7. It uncovers that the pandemic acceleration was stronger than national average for the [59–68] and especially the 69 and older age groups since early September, the latter being associated with the strongest acceleration index, as of October 25. In contrast, acceleration among the [19–28] age group was the lowest and is about half that of the [69–78]. In addition, we propose an algorithm to allocate tests among French “départements” (roughly counties), based on both the acceleration index and the feedback effect of testing. Our acceleration-based allocation differs from the actual distribution over French territories, which is population-based. We argue that both our acceleration index and our allocation algorithm are useful tools to guide public health policies as France might possibly enter a third lock-down period with indeterminate duration.
Our analysis of US state-level data on an annual frequency, from 1976 to 2008, sheds new light on a plausible causal link between infrastructure investments, namely public spending on highways, and income inequality. This causal relationship is drawn out using the number of seats in the US House of Representatives Committee on Appropriations (HRCA) as an instrument to identify quasi-random variations in state-level spending on highways. An exogenous pattern which emerges when a state gains an additional member to the HRCA is that it is allocated with new federal grants. This increase in federal transfers for infrastructure financing results in slashing of expenditures on highways and a crowding-out effect of federal funding for state investments on highways. Spending cuts on highways produced by a new HRCA member being attained by a state can unwittingly cause income inequality to rise over a short 2-year time horizon. Similar challenges with decentralized development to finance infrastructure via federal transfers to state and sub-national governments may be encountered by other industrially advanced, emerging and low-income developing economies. US data over the mentioned period reveal a strong positive correlation with state spending on highways and wages paid for construction jobs. Suggestive evidence indicates that the construction sector also plays an important role in the transmission channel from a rise in state spending on highways to lowering income inequality, albeit during specific intervals, as opposed to on a long-term basis.
Tests are crucial to know about the number of people who have fallen ill with COVID-19 and to understand in real-time whether the dynamics of the pandemic is accelerating or decelerating. But tests are a scarce resource in many countries. The key but still open question is thus how to allocate tests across sub-national levels. We provide a data-driven and operational criterion to allocate tests efficiently across regions or provinces, with the view to maximize detection of people who have been infected. We apply our criterion to Italian regions and compute the shares of tests that should go to each region, which are shown to differ significantly from the actual distribution.Mickael Degoule
This paper stresses a new channel through which global financial linkages contribute to the co‐movement in economic activity across countries. We show in a two‐country setting with borrowing constraints that international credit markets are subject to self‐fulfilling variations in the world real interest rate. Those expectation‐driven changes in the borrowing cost in turn act as global shocks that induce strong cross‐country co‐movements in both financial and real variables (such as asset prices, gross domestic product, consumption, investment, and employment). When firms around the world benefit from unexpectedly low debt repayments, they borrow and invest more, which leads to excessive supply of collateral and of loanable funds at a low interest rate, thus fueling a boom both at home and abroad. As a consequence, business cycles are synchronized internationally. Such a stylized model thus offers one way to rationalize both the existence of a world business‐cycle component, documented by recent empirical studies through dynamic factor analysis, and the factor's intimate link to global financial markets.
Under uncertainty, mean growth of, say, wealth is often defined as the growth rate of average wealth, but it can alternatively be defined as the average growth rate of wealth. We argue that stochastic stability points to the latter notion of mean growth as the theoretically relevant one. Our discussion is cast within the class of continuous-time AK-type models subject to geometric Brownian motions. First, stability concepts related to stochastic linear homogeneous differential equations are introduced and applied to the canonical AK model. It is readily shown that exponential balanced-growth paths are not robust to uncertainty. In a second application, we evaluate the quantitative implications of adopting the stochastic-stability-related concept of mean growth for the comparative statics of global diversification in the seminal model due to Obstfeld (1994).
This paper aims at clarifying the analytical conditions under which financial globalization originates welfare gains in a simple endogenous growth setting. We focus on an open-economy AK model in which the capital-deepening effect of financial globalization boosts growth in a in permanent but entails an entry cost in order to access international credit markets. We show that constrained borrowing triggers substantial welfare gains, even at small levels of international financial integration, provided that the autarkic growth rate is larger than the world interest rate. Such conditional welfare benefits boosted by stronger growth—long-run gain—arise in our preferred model without investment commitment and they range, relative to autarky, from about 2% in middle-income countries to about 13% in OECD-type countries under international financial integration. Sizeable benefits emerge despite the fact that consumption initially falls—short-run pain—which is, however, shown not to dwarf positive growth changes.
The value of land in the balance sheet of French firms correlates positively with their hiring and investment flows. To explore the relationship between these variables, we develop a macroeconomic model with firms that are subject to both credit and labor market frictions. The value of collateral is driven by the forward-looking dynamics of the land price, which reacts endogenously to fundamental and non-fundamental (sunspot) shocks. We calibrate the model to French data and find that land price shocks give rise to significant amplification and hump-shaped responses of investment, vacancies and unemployment that are in line with the data. We show that both the endogenous movements in the firms׳ discount factor and the sluggish response of the land price are key elements that drive the results.
The fluctuations of the value of land held by French firms present a very similar pattern to those of both investment and employment. This Rue de la Banque presents a model in which firms face imperfect labour and credits markets. Due to a collateral constraint for credit, the market value of land in firms’ balance sheets plays an important role in determining how much they can borrow, and thus affects their investment levels and hiring decisions. The empirical results confirm the predictions of the theoretical model. Fluctuations in land prices had an impact on the business cycle and on the dynamics of the labour market in France.
Most studies assessing animal decision-making under risk rely on probabilities that are typically larger than 10%. To study Decision-Making in uncertain conditions, we explore a novel experimental and modelling approach that aims at measuring the extent to which rats are sensitive - and how they respond - to outcomes that are both rare (probabilities smaller than 1%) and extreme in their consequences (deviations larger than 10 times the standard error). In a four-armed bandit task, stochastic gains (sugar pellets) and losses (time-out punishments) are such that extremely large - but rare - outcomes materialize or not depending on the chosen options. All rats feature both limited diversification, mixing two options out of four, and sensitivity to rare and extreme outcomes despite their infrequent occurrence, by combining options with avoidance of extreme losses (Black Swans) and exposure to extreme gains (Jackpots). Notably, this sensitivity turns out to be one-sided for the main phenotype in our sample: it features a quasi-complete avoidance of Black Swans, so as to escape extreme losses almost completely, which contrasts with an exposure to Jackpots that is partial only. The flip side of observed choices is that they entail smaller gains and larger losses in the frequent domain compared to alternatives. We have introduced sensitivity to Black Swans and Jackpots in a new class of augmented Reinforcement Learning models and we have estimated their parameters using observed choices and outcomes for each rat. Adding such specific sensitivity results in a good fit of the selected model - and simulated behaviors that are close - to behavioral observations, whereas a standard Q-Learning model without sensitivity is rejected for almost all rats. This model reproducing the main phenotype suggests that frequent outcomes are treated separately from rare and extreme ones through different weights in Decision-Making.
