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Working Papers


Archives: WP version of published papers


  • "Social Distancing, Vaccination and Evolution of COVID-19 Transmission Rates in Europe", by Alexander Chudik, M. Hashem Pesaran and Alessandro Rebucci, Cambridge Working Papers in Economics, CWPE2230, CESifo Working Paper No. 9754 May 2022.

    Abstract: This paper provides estimates of COVID-19 effective reproduction numbers and explains their evolution for selected European countries since the start of the pandemic taking account of changes in voluntary and government mandated social distancing, incentives to comply, vaccination and the emergence of new variants. Evidence based on panel data modeling indicates that the diversity of outcomes that we document may have resulted from the non-linear interaction of mandated and voluntary social distancing and the economic incentives that governments provided to support isolation. The importance of these factors declined over time, with vaccine uptake driving heterogeneity in country experiences in 2021. Our approach, also allows us to identify the basic reproduction number, R0. It is precisely estimated and differ little across countries.
    JEL Classifications: D0, F6, C4, I120, E7
    Key Words: COVID-19, multiplication factor, under-reporting, social distancing, self-isolation, SIR model, reproduction number, pandemics, vaccine.
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  • "Identification and Estimation of Categorical Random Coeficient Models", by Zhan Gao and M. Hashem Pesaran, April 2022, Cambridge Working Papers in Economics, CWPE2228

    Abstract: This paper proposes a linear categorical random coefficient model, in which the random coefficients follow parametric categorical distributions. The distributional parameters are identified based on a linear recurrence structure of moments of the random coefficients. A Generalized Method of Moments estimator is proposed, and its finite sample properties are examined using Monte Carlo simulations. The utility of the proposed method is illustrated by estimating the distribution of returns to education in the U.S. by gender and educational levels. We find that rising heterogeneity between educational groups is mainly due to the increasing returns to education for those with postsecondary education, whereas within group heterogeneity has been rising mostly in the case of individuals with high school or less education.
    JEL Classifications: C01, C21, C13, C46, J30
    Key Words: Random coefficient models, categorical distribution, return to education
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  • "Causal Effects of the Fed's Large-Scale Asset Purchases on Firms' Capital Structure, by Andrea Nocera and M. Hashem Pesaran, April 2022, Cambridge Working Papers in Economics, CWPE2224

    Abstract: This paper investigates the short- and long-term impacts of the Federal Reserve’s large-scale asset purchases (LSAPs) on the capital structure of U.S. non-financial firms. To isolate the effects of LSAPs from the impact of concurrent macroeconomic conditions, we exploit cross-industry variations in the ability of firms therein to raise external funds without exhausting their debt capacity. We show that firms’ responses to LSAPs strongly depend on the financing decisions of other peers in the same industry. The higher the proportion of firms without high debt burdens in an industry, the stronger the response of firms within the industry to the Fed’s asset purchases. Overall, our results show that LSAPs facilitated firms’ access to debt financing and that the impacts of LSAPs on firms’ capital structure are likely to be long-lasting.
    JEL Classifications: G32, E44, E52, E58
    Key Words: Capital structure, identification, interactive effects, leverage, quantitative easing, unconventional monetary policy
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  • "Forecasting with Panel Data: Estimation Uncertainty Versus Parameter Heterogeneity", by M. Hashem Pesaran, Andreas Pick and Allan Timmermann, March 2022, Cambridge Working Papers in Economics, CWPE2219

    Abstract: We develop novel forecasting methods for panel data with heterogeneous parameters and examine them together with existing approaches. We conduct a systematic comparison of their predictive accuracy in settings with different cross-sectional (N) and time (T) dimensions and varying degrees of parameter heterogeneity. We investigate conditions under which panel forecasting methods can perform better than forecasts based on individual estimates and demonstrate how gains in predictive accuracy depend on the degree of parameter heterogeneity, whether heterogeneity is correlated with the regressors, the goodness of fit of the model, and, particularly, the time dimension of the data set. We propose optimal combination weights for forecasts based on pooled and individual estimates and develop a novel forecast poolability test that can be used as a pretesting tool. Through a set of Monte Carlo simulations and three empirical applications to house prices, CPI inflation, and stock returns, we show that no single forecasting approach dominates uniformly. However, forecast combination and shrinkage methods provide better overall forecasting performance and offer more attractive risk profiles compared to individual, pooled, and random effects methods.
    JEL Classifications: C33, C53
    Key Words: Forecasting, Panel data, Heterogeneity, Forecast evaluation, Forecast combination, Shrinkage, Pooling
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  • "Revisiting the Great Ratios Hypothesis", by Alexander Chudik, M. Hashem Pesaran and Ron P. Smith, March 2022, Cambridge Working Papers in Economics, CWPE2215 and CESifo Working Paper No. 9625

    Abstract: The idea that certain economic variables are roughly constant in the long-run is an old one. Kaldor described them as stylized facts, whereas Klein and Kosobud labelled them great ratios. While such ratios are widely adopted in theoretical models in economics as conditions for balanced growth, arbitrage or solvency, the empirical literature has tended to find little evidence for them. We argue that this outcome could be due to episodic failure of cointegration, possible two-way causality between the variables in the ratios, and cross-country error dependence due to latent factors. We propose a new system pooled mean group estimator (SPMG) to deal with these features. Using this new panel estimator and a dataset spanning almost one and half centuries and seventeen countries, we find support for five out of the seven great ratios that we consider. Extensive Monte Carlo experiments also show that the SPMG estimator with bootstrapped confidence intervals stands out as the only estimator with satisfactory small sample properties.
    JEL Classifications: B40, C18, C33, C50
    Key Words: Great ratios, debt, consumption, and investment to GDP ratios, arbitrage conditions, heterogeneous panels, episodic cointegration, two-way long-run causality, error cross-sectional dependence
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  • "Climate Change and Economic Activity: Evidence from U.S. States", by Kamiar Mohaddes, Ryan N. C. Ng, M. Hashem Pesaran, Mehdi Raissi and Jui-Chung Yang, January 2022, Cambridge Working Papers in Economics, CWPE2205, CAMA Working Paper Series, vol 10/2022 and CESifo Working Paper No. 9542

    Abstract: We investigate the long-term macroeconomic effects of climate change across 48 U.S. states over the period 1963 2016 using a novel econometric strategy which links deviations of temperature and precipitation (weather) from their long-term moving-average historical norms (climate) to various state-specific economic performance indicators at the aggregate and sectoral levels. We show that climate change has a long-lasting adverse impact on real output in various states and economic sectors, and on labour productivity and employment in the United States. Moreover, in contrast to most cross-country results, our within U.S. estimates tend to be asymmetrical with respect to deviations of climate variables (including precipitation) from their historical norms.
    JEL Classifications: C33, O40, O44, O51, Q51, Q54
    Key Words: Adaptation, Climate Change, economic growth, United States
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  • "A Bias-Corrected CD Test for Error Cross-Sectional Dependence in Panel Data Models with Latent Factors", by M. Hashem Pesaran and Yimeng Xie, July 2021, Cambridge Working Papers in Economics, CWPE2158.

    Abstract: In a recent paper Juodis and Reese (2021) (JR) show that the application of the CD test proposed by Pesaran (2004) to residuals from panels with latent factors results in over-rejection and propose a randomized test statistic to correct for over-rejection, and add a screening component to achieve power. This paper considers the same problem but from a different perspective and shows that the standard CD test remains valid if the latent factors are weak, and proposes a simple bias-corrected CD test, labelled CD*, which is shown to be asymptotically normal, irrespective of whether the latent factors are weak or strong. This result is shown to hold for pure latent factor models as well as for panel regressions with latent factors. Small sample properties of the CD* test are investigated by Monte Carlo experiments and are shown to have the correct size and satisfactory power for both Gaussian and non-Gaussian errors. In contrast, it is found that JR's test tends to over-reject in the case of panels with non-Gaussian errors, and have low power against spatial network alternatives. The use of the CD* test is illustrated with two empirical applications from the literature.
    JEL Classifications: C18, C23, C55
    Key Words: Latent factor models, strong and weak factors, error cross-sectional dependence, spatial and network alternatives.
    Full Text: Bias-corrected_CD_test_July_31_2021_(YX 081721).pdf
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  • "Identifying the Effects of Sanctions on the Iranian Economy using Newspaper Coverage", by Dario Laudati and M. Hashem Pesaran, July 2021, Cambridge Working Papers in Economics, CWPE2155.

    Abstract: This paper considers how sanctions affected the Iranian economy using a novel measure of sanctions intensity based on daily newspaper coverage. It finds sanctions to have significant effects on exchange rates, inflation, and output growth, with the Iranian rial over-reacting to sanctions, followed up with a rise in inflation and a fall in output. In absence of sanctions, Iran’s average annual growth could have been around 4-5 per cent, as compared to the 3 per cent realized. Sanctions are also found to have adverse effects on employment, labor force participation, secondary and high-school education, with such effects amplified for females.
    JEL Classifications: E31, E65, F43, F51, F53, O11, O19, O53
    Key Words: Newspaper coverage, identification of direct and indirect effects of sanctions, Iran output growth, exchange rate depreciation and inflation, labor force participation and employment, secondary education, and gender bias.
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    Data and Codes:


  • "Pooled Bewley Estimator of Long Run Relationships in Dynamic Heterogenous Panels", by Alexander Chudik, M. Hashem Pesaran, and Ron P. Smith, May 2021.

    Abstract: This paper, using the Bewley (1979) transformation of the autoregressive distributed lag model, proposes a pooled Bewley (PB) estimator of long-run coefficients for dynamic panels with heterogeneous short-run dynamics, in the same setting as the widely used Pooled Mean Group (PMG) estimator. The Bewley transform enables us to obtain an analytical closed form expression for the PB, which is not available when using the maximum likelihood approach. This lets us establish asymptotic normality of PB as n, T → ∞ jointly, allowing for applications with n and T large and of the same order of magnitude, but excluding panels where T is short relative to n. In contrast, asymptotic distribution of PMG estimator was obtained for n fixed and T → ∞. Allowing for both n and T large seems to be the more relevant empirical setting, as revealed by numerous applications of the PMG estimator in the literature. Dynamic panel estimators are biased when T is not sufficiently large. Three bias corrections (simulation based, split-panel jackknife, and a combined procedure) are investigated using Monte Carlo experiments, of which the combined procedure works best in reducing bias. In contrast to PMG, PB does not weight by estimated variances, which can make it more robust in small samples, though less efficient asymptotically. The PB estimator is illustrated with an application to the aggregate consumption function estimated in the original PMG paper.
    JEL Classifications: C12, C13, C23, C33
    Key Words: Heterogeneous dynamic panels; I(1) regressors; pooled mean group estimator (PMG), Autoregressive-Distributed Lag model (ARDL), Bewley transform, bias correction, split-panel jackknife.
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    Codes and Data: /people-files/emeritus/mhp1/wp21/


  • "Factor Strengths, Pricing Errors, and Estimation of Risk Premia", by M. Hashem Pesaran and Ron P. Smith, March 2021, CESifo Working Paper No. 8947.

    Abstract: This paper examines the implications of pricing errors and factors that are not strong for the Fama-MacBeth two-pass estimator of risk premia and its asymptotic distribution when T is fixed with n → ∞, and when both n and T → ∞, jointly. While the literature just distinguishes strong and weak factors we allow for degrees of strength using a recently developed measure. Our theoretical results have important practical implications for empirical asset pricing. Pricing errors and factor strength matter for consistent estimation of risk premia and subsequent inference, thus an estimate of factor strength is required before attempting to estimate risk. Finally, using a recently developed procedure we provide rolling estimates of factor strengths for the five Fama-French factors, and show that only the market factor can be viewed as strong.
    JEL Classifications: C380, G120
    Key Words: factor strength, pricing errors, risk premia, Fama and MacBeth two-pass estimators, Fama-French factors, panel R2.
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  • "COVID-19 Time-varying Reproduction Numbers Worldwide: An Empirical Analysis of Mandatory and Voluntary Social Distancing", by Alexander Chudik, M. Hashem Pesaran and Alessandro Rebucci, March 2021.

    Abstract: This paper estimates time-varying COVID-19 reproduction numbers worldwide solely based on the number of reported infected cases, allowing for under-reporting. Estimation is based on a moment condition that can be derived from an agent-based stochastic network model of COVID-19 transmission. The outcomes in terms of the reproduction number and the trajectory of per-capita cases through the end of 2020 are very diverse. The reproduction number depends on the transmission rate and the proportion of susceptible population, or the herd immunity effect. Changes in the transmission rate depend on changes in the behavior of the virus, reflecting mutations and vaccinations, and changes in people's behavior, reflecting voluntary or government mandated isolation. Over our sample period, neither mutation nor vaccination are major factors, so one can attribute variation in the transmission rate to variations in behavior. Evidence based on panel data models explaining transmission rates for nine European countries indicates that the diversity of outcomes resulted from the non-linear interaction of mandatory containment measures, voluntary precautionary isolation, and the economic incentives that governments provided to support isolation. These effects are precisely estimated and robust to various assumptions. As a result, countries with seemingly different social distancing policies achieved quite similar outcomes in terms of the reproduction number. These results imply that ignoring the voluntary component of social distancing could introduce an upward bias in the estimates of the effects of lock-downs and support policies on the transmission rates.
    JEL Classifications: D0, F6, C4, I120, E7
    Key Words: COVID-19, SIR model, epidemics, multiplication factor, under-reporting, social distancing, self-isolation.
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  • "Variable Selection and Forecasting in High Dimensional Linear Regressions with Parameter Instability", by Alexander Chudik, M. Hashem Pesaran and Mahrad Sharifvaghe, July 2020, revised April 2021.

    Abstract: This paper is concerned with the problem of variable selection and forecasting in the presence of parameter instability. There are a number of approaches proposed for forecasting in the presence of time-varying parameters, including the use of rolling windows and exponential down-weighting. However, these studies start with a given model specification and do not consider the problem of variable selection, which is complicated by time variations in the effects of signals on target variables. In this study we investigate whether or not we should use weighted observations at the variable selection stage in the presence of parameter instability, particularly when the number of potential covariates is large. Amongst the extant variable selection approaches we focus on the recently developed One Covariate at a time Multiple Testing (OCMT) method. This procedure allows a natural distinction between the selection and forecasting stages. We establish three main theorems on selection, estimation post selection, and in-sample fit. These theorems provide justification for using the full (not down-weighted) sample at the selection stage of OCMT and down-weighting of observations only at the forecasting stage (if needed). The benefits of the proposed method are illustrated by empirical applications to forecasting monthly stock market returns and quarterly output growths.
    JEL Classifications: C22, C52, C53, C55
    Key Words: Time-varying parameters, high-dimensional, multiple testing, variable selection, Lasso, one covariate at a time multiple testing (OCMT), forecasting, monthly returns, Dow Jones
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  • "The Role of Factor Strength and Pricing Errors for Estimation and Inference in Asset Pricing Models", by M. Hashem Pesaran and Ron P. Smith, CESifo Working Paper No. tbc, October 2019.

    Abstract: In this paper we are concerned with the role of factor strength and pricing errors in asset pricing models, and their implications for identification and estimation of risk premia. We establish an explicit relationship between the pricing errors and the presence of weak factors that are correlated with stochastic discount factor. We introduce a measure of factor strength, and distinguish between observed factors and unobserved factors. We show that unobserved factors matter for pricing if they are correlated with the discount factor, and relate the strength of the weak factors to the strength (pervasiveness) of non-zero pricing errors. We then show, that even when the factor loadings are known, the risk premia of a factor can be consistently estimated only if it is strong and if the pricing errors are weak. Similar results hold when factor loadings are estimated, irrespective of whether individual returns or portfolio returns are used. We derive distributional results for two pass estimators of risk premia, allowing for non-zero pricing errors. We show that for inference on risk premia the pricing errors must be sufficiently weak. We consider both when n (the number of securities) is large and T (the number of time periods) is short, and the case of large n and T. Large n is required for consistent estimation of risk premia, whereas the choice of short T is intended to reduce the possibility of time variations in the factor loadings. We provide monthly rolling estimates of the factor strengths for the three Fama-French factors over the period 1989-2018.
    JEL Classifications: C38, G12
    Key Words: Arbitrage Pricing Theory, APT, factor strength, identification of risk premia, two-pass regressions, Fama-French factors.
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  • "Short T Dynamic Panel Data Models with Individual, Time and Interactive Effects", by Kazuhiko Hayakawa, M. Hashem Pesaran and L. Vanessa Smith, September 2018, revised July 2021

    Abstract: This paper proposes a transformed quasi maximum likelihood (TQML) estimator for short T dynamic fixed effects panel data models allowing for interactive effects through a multi-factor error structure. The proposed estimator is robust to the heterogeneity of the initial values and common unobserved effects, whilst at the same time allowing for standard fixed and time effects. It is applicable to both stationary and unit root cases. The order condition for identification of the number of interactive effects is established, and conditions are derived under which the parameters are almost surely locally identified. It is shown that global identification in the presence of the lagged dependent variable cannot be guaranteed. The TQML estimator is proven to be consistent and asymptotically normally distributed. A sequential multiple testing likelihood ratio procedure is also proposed for estimation of the number of factors which is shown to be consistent. Finite sample results obtained from Monte Carlo simulations show that the proposed procedure for determining the number of factors performs very well and the TQML estimator has small bias and RMSE, and correct empirical size in most settings. The practical use of the TQML approach is demonstrated by means of two empirical illustrations from the literature on cross county crime rates and cross country growth regressions.
    JEL Classifications: C12, C13, C23.
    Key Words: short T dynamic panels, unobserved common factors, quasi maximum likelihood, interactive effects, multiple testing, sequential likelihood ratio tests, crime rate, growth regressions.
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  • "A Spatiotemporal Equilibrium Model of Migration and Housing Interlinkages", by Wukuang Cun and M. Hashem Pesaran. April 2018, revised September 2021

    Abstract: This paper develops and solves a spatiotemporal equilibrium model in which regional wages and house prices are determined jointly with location-to-location migration flows. The agent's optimal location choice and the resultant migration process are shown to be Markovian, with the transition probabilities across all location pairs given as non-linear functions of wage and housing cost differentials, endogenously responding to migration flows. The model can be used for the analysis of spatial distribution of population, income, and house prices, as well as for the analysis of the entire dynamic process of shock spill-over effects in regional economies through location-to-location migration. The model is estimated on a panel of 48 mainland U.S. states and the District of Columbia over the training sample (1976-1999) and is shown to fit the data well over the evaluation sample (2000-2014). The estimated model is then used to analyze the size and speed of spatial spill-over effects by computing spatiotemporal impulse responses of positive productivity and land-supply shocks to California, Texas, and Florida. The sensitivity of the results to migration elasticity, housing depreciation rate and local land supply conditions is also investigated.
    JEL Classifications: E0, R23, R31
    Key Words: location choice, joint determination of migration and house prices, spatiotemporal impulse responses, land-use deregulation, counterfactual exercise, population allocation, productivity and land supply shocks, California, Texas and Florida.
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  • "Testing for Alpha in Linear Factor Pricing Models with a Large Number of Securities", by M. Hashem Pesaran and Takashi Yamagata, March 2017, revised January 2018

    Abstract: This paper considers tests of zero pricing errors for the linear factor pricing model when the number of securities, N, can be large relative to the time dimension, T, of the return series. We focus on class of tests that are based on Student t tests of individual securities which have a number of advantages over the existing standardised Wald type tests, and propose a test procedure that allows for non-Gaussianity and general forms of weakly cross correlated errors. It does not require estimation of an invertible error covariance matrix, it is much faster to implement, and is valid even if N is much larger than T. Monte Carlo evidence shows that the proposed test performs remarkably well even when T = 60 and N = 5; 000. The test is applied to monthly returns on securities in the S&P 500 at the end of each month in real time, using rolling windows of size 60. Statistically signifi…cant evidence against Sharpe-Lintner CAPM and Fama-French three factor models are found mainly during the recent fi…nancial crisis. Also we fi…nd a signifi…cant negative correlation between a twelve-months moving average p-values of the test and excess returns of long/short equity strategies (relative to the return on S&P 500) over the period November 1994 to June 2015, suggesting that abnormal pro…ts are earned during episodes of market ineffiencies.
    JEL Classifications: C12, C15, C23, G11, G12
    Key Words: CAPM, Testing for alpha, Weak and spatial error cross-sectional dependence, S&P 500 securities, Long/short equity strategy.
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  • "Business Cycle Effects of Credit Shocks in a DSGE Model with Firm Defaults", by M. Hashem Pesaran and TengTeng Xu, CWPE Working paper. No. 1159, CESifo Working Paper No. 3609, IZA Discussion Paper No. 6027, October 2011, revised April 2016

    Abstract: This paper proposes a new theoretical framework for the analysis of the relationship between credit shocks, firm defaults and volatility. The key feature of the modelling approach is to allow for the possibility of default in equilibrium. The model is then used to study the impact of credit shocks on business cycle dynamics. It is assumed that firms are identical ex ante but differ ex post due to different realizations of firm-specific technology shocks, possibly leading to default by some firms. The implications of firm defaults for the balance sheets of households and banks and their subsequent impacts on business uctuations are investigated within a dynamic stochastic general equilibrium framework. Results from a calibrated version of the model suggest that, in the steady state, a firm's default probability rises with its leverage ratio and the level of uncertainty in the economy. A positive credit shock, defined as a rise in the loan-to-deposit ratio, increases output, consumption, hours and productivity, and reduces the spread between loan and deposit rates. Interestingly, the effects of the credit shock tend to be highly persistent, even without price rigidities and habit persistence in consumption behavior.
    JEL Classifications: E32, E44, E50, G21.
    Key Words: Firm Defaults; Credit Shocks; Financial Intermediation; Interest Rate Spread; Uncertainty.
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    Supplement: 5Oct2011_Supplement.pdf


  • "Optimality and Diversifiability of Mean Variance and Arbitrage Pricing Portfolios", by M. Hashem Pesaran, and Paolo Zaffaroni, CESifo Working Papers No. 2857, October, 2009

    Abstract: This paper investigates the limit properties of mean-variance (mv) and arbitrage pricing (ap) trading strategies using a general dynamic factor model, as the number of assets diverge to infinity. It extends the results obtained in the literature for the exact pricing case to two other cases of asymptotic no-arbitrage and the unconstrained pricing scenarios. The paper characterizes the asymptotic behaviour of the portfolio weights and establishes that in the non-exact pricing cases the ap and mv portfolio weights are asymptotically equivalent and, moreover, functionally independent of the factors conditional moments. By implication, the paper sheds light on a number of issues of interest such as the prevalence of short-selling, the number of dominant factors and the granularity property of the portfolio weight.
    JEL Classifications: Large Portfolios, Factor Models, Mean-Variance Portfolio, Arbitrage Pricing, Market (Beta) Neutrality, Well Diversification.
    Key Words: C32, C52, C53, G11.
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