Nadine McCloud, PhD
Thinker. Researcher. Educator.
A Researcher’s Bio
A Life of Learning
Dr. Nadine McCloud is a Senior Lecturer in the Department of Economics at The University of the West Indies at Mona. Her main research interests are econometric theory - with emphasis on nonparametric estimation and specification testing in time-series, cross-sectional and panel data models - Bayesian econometrics, matrix analysis, economic development and the political economy, and applied econometrics. Her recent theoretical focus includes deriving asymptotic properties for semiparametric system of simultaneous equation models with instrumental variables and degrees of freedom for different nonparametric regression models. Her emphasis is also on using semiparametric tools to delve into cross-country patterns of institution-induced heterogeneity in the effect of foreign direct investment flows on different aspects of economic development. She has attained publications in both economics and mathematics journals. Her research articles have appeared in the International Economic Review and Journal of the Royal Statistical Society.
Dr. McCloud received her BSc and MPhil in Mathematics from The University of the West Indies at Mona, and her PhD in Economics from the State University of New York at Binghamton. She has been a Fulbright Visiting Research Scholar at Cornell University. She has held short research stints at Humboldt University in Germany, Purdue University, University of Miami, and Xiamen University in China. Dr. McCloud is a member of the editorial board of The Journal of International Trade & Economic Development. She is also an Associate Editor of the International Journal of Finance & Economics and a Senior Co-Editor of Advances in Econometrics. Additionally, she is an Appointed Member of the Monetary Policy Committee, Bank of Jamaica, and a member of the Board of Directors for the Planning Institute of Jamaica.
"To each there comes a time in their lifetime a special moment when they are figuratively tapped on the shoulder and offered the chance to do a very special thing, unique to them and fitted to their talents. What a tragedy if that moment finds them unprepared or unqualified for that which could have been their finest hour." - Sir W. Churchill
Selected Published Work
Selected Journal Articles
International Economic Review, (2011), Vol. 52 (4), pp. 991-1037
We introduce a class of generally applicable specification tests for constant and dynamic structures of conditional correlations in multivariate GARCH models. The tests are robust to the presence of time-varying higher-order conditional moments of unknown form and are pure significance tests. The tests can identify linear and nonlinear misspecifications in conditional correlations. Our approach does not necessitate a particular parameter estimation method and distributional assumption on the error process. The asymptotic distribution of the tests is invariant to the uncertainty in parameter estimation. We assess the finite sample performance of our tests using simulated and real data.
Journal of the Royal Statistical Society: Series A, (2012), Vol. 175, pp. 83-105
We investigate empirically the existence of a heterogeneous relationship between foreign direct investment (FDI) and economic growth across developing countries. We argue that, across countries, differences in institutional quality are correlated with heterogeneous absorptive capacities and hence a heterogeneous FDI–growth relationship. Our empirical results show substantial heterogeneity in the FDI–growth relationship. We find that controlling for certain measures of institutional quality reduces the degree of heterogeneity. These findings question the orthodox assumption of a homogeneous return to FDI in the existing empirical literature and highlight the importance of specific aspects of institutional quality in the FDI–growth relationship.
European Journal of Political Economy, (2018), 55, pp. 258-283.
The flow of foreign direct investment (FDI) has increased the challenges governments face in carrying out their fiscal responsibilities. A country's system of law and order enables or constrains the implementation of government policies, and consequently influences whether the size of government responds to changes in FDI inflows and outflows. We test this hypothesis by fitting a semiparametric model of government consumption to a panel of developed and developing countries with within-country variation. Over a short data frequency, the average compensating response of governments in developing countries to an increase in FDI inflows is larger by a factor of five than that of developed countries. These significant level effects of FDI inflows are driven by law and order and are adjusted for differences in per capita income across countries. The larger the compensating response of a government, the bigger is the constraining effect of a stronger system of law and order. The efficiency hypothesis seems empirically valid for developing countries with a moderate system of law and order. Over a long data frequency, we find a strong (negative) link between FDI inflows and government consumption, and increases in law and order weaken this link. For both data frequencies, FDI outflows have no level effect on government consumption, whereas the empirical regularity of strong and robust inertia in government consumption exists in all countries.
Journal of Econometric Methods, (2018), 7(1), 20160008.
We characterize the types of interactions between foreign direct investment (FDI) and economic growth and analyze the effect of institutional quality on such interactions. To do this analysis, we develop a class of instrument-based semiparametric system of simultaneous equations estimators for panel data and prove that our estimators are consistent and asymptotically normal. Our new methodological tool suggests that across developed and developing economies, causal, heterogeneous symbiosis and commensalism are the most dominant types of interactions between FDI and economic growth. Higher institutional quality facilitates, impedes or has no effect on the interactions between FDI and economic growth.
Computational Statistics & Data Analysis, (2020), 143, 106843.
The hat matrix maps the vector of response values in a regression to its predicted counterpart. The trace of this hat matrix is the workhorse for calculating the effective number of parameters in both parametric and nonparametric regression settings. Drawing on the regression literature, the standard kernel density estimate is transformed to mimic a regression estimate thus allowing the extraction of a usable hat matrix for calculating the effective number of parameters of the kernel density estimate. Asymptotic expressions for the trace of this hat matrix are derived under standard regularity conditions for mixed, continuous, and discrete densities. Simulations validate the theoretical contributions. Several empirical examples demonstrate the usefulness of the method suggesting that calculating the effective number of parameters of a kernel density estimator may be useful in interpreting differences across estimators.
“Calculating Degrees of Freedom in Multivariate Local Polynomial Regression”
(joint with Christopher Parmeter, University of Miami)
Journal of Statistical Planning and Inference, (2021), 210, pp. 141-160.
The matrix that transforms the response variable in a regression to its predicted value is commonly referred to as the hat matrix. The trace of the hat matrix is a standard metric for calculating degrees of freedom. Nonparametric-based hat matrices do not enjoy all properties of their parametric counterpart in part owing to the fact that the former do not always stem directly from a traditional ANOVA decomposition. In the multivariate, local polynomial setup with a mix of continuous and discrete covariates, which include some irrelevant covariates, we formulate asymptotic expressions for the trace of the resultant non-ANOVA and ANOVA-based hat matrix from the estimator of the unknown conditional mean. % and derivatives, as well as asymptotic expressions for the trace of the ANOVA-based hat matrix from the estimator of the unknown conditional mean. The asymptotic expression of the trace of the non-ANOVA hat matrix associated with the conditional mean estimator is equal up to a linear combination of kernel-dependent constants to that of the ANOVA-based hat matrix. Additionally, we document that the trace of the ANOVA-based hat matrix converges to 0 in any setting where the bandwidths diverge. This attrition outcome can occur in the presence of irrelevant continuous covariates or it can arise when the underlying data generating process is in fact of polynomial order. Simulated examples demonstrate that our theoretical contributions are valid in finite-sample settings.
“Domestic Interest Rates and Foreign Direct Investment under Institutional Uncertainty”
(joint with Michael Delgado, Purdue University)
Review of World Economics, (2022), 158, pp. 467-491.
"Does Inflation Targeting matter for International Trade? A Synthetic Control Analysis"
(joint with Ajornie Taylor)
Empirical Economics, Forthcoming.
"Does Domestic Investment respond to Inflation Targeting? A Synthetic Control Investigation"
International Economics, (2022), 169, pp. 98-134.
Working Papers and Work In Progress
“An Instrumental-Variable Approach to Estimation and Inference of Conditional Distribution Models with Endogeneity,” (joint with Yongmiao Hong, Cornell University)
“Stochastic Search Variable Selection and Instrumental Variables in Bayesian Linear Models”
“Specification Tests for A Class of Semiparametric Models”
“Improved Generalized Likelihood Ratio Tests for Spectral Density,” (joint with Yongmiao Hong, Cornell University)
“An Improved Higher-Order Test for Gaussianity”
“Are Openness and Corruption Substitutes or Complements for Inflation Determination?”
“Fiscal Policy and Public Debt in a Model with Corruption”
“Do Capital flows have (Dis)-Inflationary Effects?”
Knowledge for Every Level
Mathematics for Economists (PhD level), Department of Economics, The University of the West Indies at Mona, Semester I 2019
Econometrics I, Department of Economics, The University of the West Indies at Mona, Semester I 2008, 2009, 2010, 2014, 2015, 2016, 2017, 2018, 2019
Macroeconomic Theory II, Department of Economics, The University of the West Indies at Mona, Semester II 2014, 2015, 2016, 2017, 2018
Econometrics II, Department of Economics, The University of the West Indies at Mona, Semester II 2011
Mathematical Analysis for Economists, Department of Economics, State University of New York at Binghamton, Semester I 2006
Applied Econometrics, Department of Economics, The University of the West Indies at Mona, Semester II 2009, 2011, 2014, 2015, 2016, 2017, 2018
Statistical Methods I, Department of Economics, The University of the West Indies at Mona, Semester I 2014, 2015, 2016
Econometrics, Department of Economics, The University of the West Indies at Mona, Semester I 2008, 2009, 2010
Operations Research I, Department of Economics, The University of the West Indies at Mona, Semester I 2008
Mathematical Economic Analysis, Department of Economics, State University of New York at Binghamton, Semester II 2007
Matrix Algebra, Department of Economics, The University of the West Indies at Mona, Jamaica, Summer 2002, 2003, 2004, Semester I 2001
Calculus I, Department of Economics, The University of the West Indies at Mona, Jamaica, Semester I 2002