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Articles 91 - 120 of 123
Full-Text Articles in Econometrics
Modeling The Nigerian Inflation Rates Using Periodogram And Fourier Series Analysis, Chukwuemeka O. Omekara,, Emmanuel J. Ekpenyong, Micheal P. Ekerete
Modeling The Nigerian Inflation Rates Using Periodogram And Fourier Series Analysis, Chukwuemeka O. Omekara,, Emmanuel J. Ekpenyong, Micheal P. Ekerete
CBN Journal of Applied Statistics (JAS)
This work considers the application of Periodogram and Fourier Series Analysis to model all-items monthly inflation rates in Nigeria from 2003 to 2011. The main objectives are to identify inflation cycles, fit a suitable model to the data and make forecasts of future values. To achieve these objectives, monthly all-items inflation rates for the period were obtained from the Central Bank of Nigeria (CBN) website. Periodogram and Fourier series methods of analysis are used to analyze the data. Based on the analysis, it was found that inflation cycle within the period was fifty one (51) months, which coincides with the …
Nigerian Stock Index: A Search For Optimal Garch Model Using High Frequency Data, Olaoluwa Simon Yaya
Nigerian Stock Index: A Search For Optimal Garch Model Using High Frequency Data, Olaoluwa Simon Yaya
CBN Journal of Applied Statistics (JAS)
This paper attempts to fit the best Generalized Autoregressive Conditional Heteroscedastic (GARCH) model for All Share Index (ASI) of Nigerian Stock Exchange (NSE) returns. A search is made on various GARCH variants specified on the assumptions of stationarity and asymmetry. Fractionally integrated types are also considered to capture the possibility of return series having property of long range dependency. The parameter estimations are carried out on the assumptions of normality and non-normality of GARCH innovations, with models and forecasts evaluated using information criteria and loss functions respectively. Under normality assumption, Hyperbolic GARCH (HYGARCH(1,d,1)) model is selected and Integrated GARCH (IGARCH(1,1)) …
Time Series Modeling Of Nigeria External Reserves, Iheanyichukwu S. Iwueze, Eleazar C. Nwogu, Valentine U. Nlebedim
Time Series Modeling Of Nigeria External Reserves, Iheanyichukwu S. Iwueze, Eleazar C. Nwogu, Valentine U. Nlebedim
CBN Journal of Applied Statistics (JAS)
This paper discusses the levels and trend of external reserves in Nigeria. The relevance of this lies in the fact that it could help to monitor the reserves and throw early warning signal about any economic crisis. Monthly data on Nigeria external reserves for the period January 1999 to December, 2008 derived from the 2008 CBN Statistical Bulletin was analyzed using ARIMA model. Results of the analyses show that (i) the data requires logarithmic transformation to stabilize the variance and make the distribution normal (ii) the appropriate model that best describes the pattern in the transformed data is the Autoregressive- …
A Markov Decision Process Approach To Optimal Control Of A Multi-Level Hierarchical Manpower System, Akaninyene U. Udom
A Markov Decision Process Approach To Optimal Control Of A Multi-Level Hierarchical Manpower System, Akaninyene U. Udom
CBN Journal of Applied Statistics (JAS)
A recurrent problem in manpower control is how to attain the desired structural configuration in an optimal way, since it is possible to reach a desired structural configuration using different control inputs. The major aim of this paper is to develop a Markov Decision Process for optimal control of a Multi-level Hierarchical Manpower System (MHMS) by promotion and interdepartmental transfers. This is examined under control by intervention and contraction cost Markov Decision Process.
State Level Earned Income Tax Credit’S Effects On Race And Age: An Effective Poverty Reduction Policy, Anthony J. Barone
State Level Earned Income Tax Credit’S Effects On Race And Age: An Effective Poverty Reduction Policy, Anthony J. Barone
CMC Senior Theses
In this paper, I analyze the effectiveness of state level Earned Income Tax Credit programs on improving of poverty levels. I conducted this analysis for the years 1991 through 2011 using a panel data model with fixed effects. The main independent variables of interest were the state and federal EITC rates, minimum wage, gross state product, population, and unemployment all by state. I determined increases to the state EITC rates provided only a slight decrease to both the overall white below-poverty population and the corresponding white childhood population under 18, while both the overall and the under-18 black population for …
Variable Selection In Nonparametric And Semiparametric Regression Models, Liangjun Su, Yonghui Zhang
Variable Selection In Nonparametric And Semiparametric Regression Models, Liangjun Su, Yonghui Zhang
Research Collection School Of Economics
This chapter reviews the literature on variable selection in nonparametric and semiparametric regression models via shrinkage. We highlight recent developments on simultaneous variable selection and estimation through the methods of least absolute shrinkage and selection operator (Lasso), smoothly clipped absolute deviation (SCAD) or their variants, but restrict our attention to nonparametric and semiparametric regression models. In particular, we consider variable selection in additive models, partially linear models, functional/varying coefficient models, single index models, general nonparametric regression models, and semiparametric/nonparametric quantile regression models.
Contributions Of Financial Sector Reforms And Credit Supply To Nigerian Agricultural Sector (1978-2009), Anthony O. Onoja, M. E. Onu, S. Ajodo-Ohiemi
Contributions Of Financial Sector Reforms And Credit Supply To Nigerian Agricultural Sector (1978-2009), Anthony O. Onoja, M. E. Onu, S. Ajodo-Ohiemi
CBN Journal of Applied Statistics (JAS)
This study analyzed the trends and pattern of institutional credit supply to agriculture during pre- and post-financial reforms along with their determinants. It then compared the effects of reform policies on access to institutional credits in Nigerian agricultural sector before and after the reforms (1978 - 1985; and 1986 -2009). Relying mainly on time series data from CBN and NBS, it used ordinary least squares method (linear, semi-log and double log) to model the determinants of banking sector lending to the agricultural sector during the review period. The models were subjected to several econometric tests before accepting one. Chow test …
Determinants Of Foreign Reserves In Nigeria: An Autoregressive Distributed Lag Approach, David Irefin, Baba N. Yaaba
Determinants Of Foreign Reserves In Nigeria: An Autoregressive Distributed Lag Approach, David Irefin, Baba N. Yaaba
CBN Journal of Applied Statistics (JAS)
On global scale, central banks’ holdings of foreign reserves have escalated sharply in recent years. World international reserves holdings have risen significantly from US$1.2 trillion in 1995 to nearly US$10.0 trillion in June 2011. Dominant among these reserves are concentrated in the hands of few countries. Ten major holders of foreign reserves are mostly from Asia. Oil exporting countries in Africa and the Middle East are not left out in this trend. Nigeria’s foreign reserves rose from US$5.5 billion in 1999 to US$62.40 billion in July 2008, making Nigeria the twenty-fourth largest reserves holder in the world. This pace of …
Effects Of Exchange Rate Movements On Economic Growth In Nigeria, Eme O. Akpan, Johnson A. Atan
Effects Of Exchange Rate Movements On Economic Growth In Nigeria, Eme O. Akpan, Johnson A. Atan
CBN Journal of Applied Statistics (JAS)
This study investigates the effect of exchange rate movements on real output growth in Nigeria. Based on quarterly series for the period 1986 to 2010, the paper examines the possible direct and indirect relationship between exchange rates and GDP growth. The relationship is derived in two ways using a simultaneous equations model within a fully specified (but small) macroeconomic model. A Generalised Method of Moments (GMM) technique was explored. The estimation results suggest that there is no evidence of a strong direct relationship between changes in exchange rate and output growth. Rather, Nigeria’s economic growth has been directly affected by …
Exchange Rate Volatility In Nigeria: Consistency, Persistency & Severity Analyses, Babatunde Adeoye, Akinwande A. Atanda
Exchange Rate Volatility In Nigeria: Consistency, Persistency & Severity Analyses, Babatunde Adeoye, Akinwande A. Atanda
CBN Journal of Applied Statistics (JAS)
The adoption of the International Monetary Fund (IMF) Structural Adjustment Programme (SAP) in 1986 resulted in the transition from fixed exchange rate regime to floating exchange rate regime in Nigeria. Ever since, the exchange rate of naira vis-à-vis the U.S dollar has attained varying rates all through different time horizons. On this basis, this study examines the consistency, persistency, and severity (degree) of volatility in exchange rate of Nigerian currency (naira) vis-a-vis the United State dollar using monthly time series data from 1986 to 2008. The standard Purchasing Power Parity (PPP) model was used to analyze the long-run consistency of …
Foreign Private Investment And Economic Growth In Nigeria: A Cointegrated Var And Granger Causality Analysis, F. Z. Abdullahi, S. Ladan, Haruna R. Bakari
Foreign Private Investment And Economic Growth In Nigeria: A Cointegrated Var And Granger Causality Analysis, F. Z. Abdullahi, S. Ladan, Haruna R. Bakari
CBN Journal of Applied Statistics (JAS)
This research uses a cointegration VAR model to study the contemporaneous long-run dynamics of the impact of Foreign Private Investment (FPI), Interest Rate (INR) and Inflation rate (IFR) on Growth Domestic Products (GDP) in Nigeria for the period January 1970 to December 2009. The Unit Root Test suggests that all the variables are integrated of order 1. The VAR model was appropriately identified using AIC information criteria and the VECM model has exactly one cointegration relation. The study further investigates the causal relationship using the Granger causality analysis of VECM which indicates a uni-directional causality relationship between GDP and FDI …
Banking Sector Credit And Economic Growth In Nigeria: An Empirical Investigation, Aniekan O. Akpansung, Sikiru J. Babalola
Banking Sector Credit And Economic Growth In Nigeria: An Empirical Investigation, Aniekan O. Akpansung, Sikiru J. Babalola
CBN Journal of Applied Statistics (JAS)
The paper examines the relationship between banking sector credit and economic growth in Nigeria over the period 1970-2008. The causal links between the pairs of variables of interest were established using Granger causality test while a Two-Stage Least Squares (TSLS) estimation technique was used for the regression models. The results of Granger causality test show evidence of unidirectional causal relationship from GDP to private sector credit (PSC) and from industrial production index (IND) to GDP. Estimated regression models indicate that private sector credit impacts positively on economic growth over the period of coverage in this study. However, lending (interest) rate …
Neither The Washington Nor Beijing Consensus: Developmental Models To Fit African Realities And Cultures, Sanusi L. Sanusi
Neither The Washington Nor Beijing Consensus: Developmental Models To Fit African Realities And Cultures, Sanusi L. Sanusi
CBN Journal of Applied Statistics (JAS)
No abstract provided.
Empirical Methods For Predicting Student Retention- A Summary From The Literature, Matt Bogard
Empirical Methods For Predicting Student Retention- A Summary From The Literature, Matt Bogard
Economics Faculty Publications
The vast majority of the literature related to the empirical estimation of retention models includes a discussion of the theoretical retention framework established by Bean, Braxton, Tinto, Pascarella, Terenzini and others (see Bean, 1980; Bean, 2000; Braxton, 2000; Braxton et al, 2004; Chapman and Pascarella, 1983; Pascarell and Ternzini, 1978; St. John and Cabrera, 2000; Tinto, 1975) This body of research provides a starting point for the consideration of which explanatory variables to include in any model specification, as well as identifying possible data sources. The literature separates itself into two major camps including research related to the hypothesis testing …
Empirical Methods-A Review: With An Introduction To Data Mining And Machine Learning, Matt Bogard
Empirical Methods-A Review: With An Introduction To Data Mining And Machine Learning, Matt Bogard
Economics Faculty Publications
This presentation was part of a staff workshop focused on empirical methods and applied research. This includes a basic overview of regression with matrix algebra, maximum likelihood, inference, and model assumptions. Distinctions are made between paradigms related to classical statistical methods and algorithmic approaches. The presentation concludes with a brief discussion of generalization error, data partitioning, decision trees, and neural networks.
A Note On The Interpretation Of Scale Values In Multidimensional Scaling Growth Analysis, Cody Ding
A Note On The Interpretation Of Scale Values In Multidimensional Scaling Growth Analysis, Cody Ding
Education Sciences and Professional Programs Faculty Works
No abstract provided.
Estimation And Forecasting Of Dynamic Conditional Covariance: A Semiparametric Multivariate Model, Xiangdong Long, Liangjun Su, Aman Ullah
Estimation And Forecasting Of Dynamic Conditional Covariance: A Semiparametric Multivariate Model, Xiangdong Long, Liangjun Su, Aman Ullah
Research Collection School Of Economics
We propose a semiparametric conditional covariance (SCC) estimator that combines the first-stage parametric conditional covariance (PCC) estimator with the second-stage nonparametric correction estimator in a multiplicative way. We prove the asymptotic normality of our SCC estimator, propose a nonparametric test for the correct specification of PCC models, and study its asymptotic properties. We evaluate the finite sample performance of our test and SCC estimator and compare the latter with that of PCC estimator, purely nonparametric estimator, and Hafner, Dijk, and Franses’s (2006) estimator in terms of mean squared error and Value-at-Risk losses via simulations and real data analyses.
Model Selection In Validation Sampling Data: An Asymptotic Likelihood-Based Lasso Approach, Chenlei Leng, Denis H. Y. Leung
Model Selection In Validation Sampling Data: An Asymptotic Likelihood-Based Lasso Approach, Chenlei Leng, Denis H. Y. Leung
Research Collection School Of Economics
We propose an asymptotic likelihood-based LASSO approach for model selection in regression analysis when data are subject to validation sampling. The method makes use of an initial estimator of the regression coefficients and their asymptotic covariance matrix to form an asymptotic likelihood. This ``working'' objective function facilitates the formulation of the LASSO and the implementation of a fast algorithm. Our method circumvents the need to use a likelihood set-up that requires full distributional assumptions about the data. We show that the resulting estimator is consistent in model selection and that the method has lower prediction errors than a model that …
Nonparametric Testing For Asymmetric Information, Liangjun Su, Martin Spindler
Nonparametric Testing For Asymmetric Information, Liangjun Su, Martin Spindler
Research Collection School Of Economics
Asymmetric information is an important phenomenon in many markets and in particular in insurance markets. Testing for asymmetric information has become a very important issue in the literature in the last two decades. Almost all testing procedures that are used in empirical studies are parametric, which may yield misleading conclusions in the case of misspecification of either functional or distributional relationships among the variables of interest. Motivated by the literature on testing conditional independence, we propose a new nonparametric test for asymmetric information which is applicable in a variety of situations. We demonstrate the test works reasonably well through Monte …
Improving The Teaching Of Econometrics At Pace University Using Stata, Gregory Colman
Improving The Teaching Of Econometrics At Pace University Using Stata, Gregory Colman
Cornerstone 3 Reports : Interdisciplinary Informatics
The goal of this grant was to improve the teaching of econometrics at Pace using the computer program, Stata, the most widely-used econometrics software among applied economists.
Numerical Analysis Of Non-Constant Pure Rate Of Time Preference: A Model Of Climate Policy, Tomoki Fujii, Larry Karp
Numerical Analysis Of Non-Constant Pure Rate Of Time Preference: A Model Of Climate Policy, Tomoki Fujii, Larry Karp
Research Collection School Of Economics
When current decisions affect welfare in the far-distant future, as with climate change, the use of a declining pure rate of time preference (PRTP) provides potentially important modeling flexibility. The difficulty of analyzing models with non-constant PRTP limits their application. We describe and provide software (available online) to implement an algorithm to numerically obtain a Markov perfect equilibrium for an optimal control problem with non-constant PRTP. We apply this software to a simplified version of the numerical climate change model used in the Stern Review. For our calibration, the policy recommendations are less sensitive to the PRTP than widely believed.
Bayesian Analysis Of Structural Credit Risk Models With Microstructure Noises, Shirley J. Huang, Jun Yu
Bayesian Analysis Of Structural Credit Risk Models With Microstructure Noises, Shirley J. Huang, Jun Yu
Research Collection School Of Economics
In this paper a Markov chain Monte Carlo (MCMC) technique is developed for the Bayesian analysis of structural credit risk models with microstructure noises. The technique is based on the general Bayesian approach with posterior computations performed by Gibbs sampling. Simulations from the Markov chain, whose stationary distribution converges to the posterior distribution, enable exact ¯nite sample inferences of model parameters. The exact inferences can easily be extended to latent state variables and any nonlinear transformation of state variables and parameters, facilitating practical credit risk applications. In addition, the comparison of alternative models can be based on deviance information criterion …
A Semiparametric Stochastic Volatility Model, Jun Yu
A Semiparametric Stochastic Volatility Model, Jun Yu
Research Collection School Of Economics
This paper examines how volatility responds to return news in the context of stochastic volatility (SV) using a nonparametric method. The correlation structure in the classical leverage SV model is generalized based on a linear spline. In the new model the correlation between the return innovation and volatility innovation is dependent on the type of news arrived to the market. Theoretical properties of the proposed model are examined. A simulation-based maximum likelihood method is developed to estimate the new model. Simulations show that the estimation method provides reliable parameter estimates. The new model is fitted to daily and weekly data …
The Impact Of Being Born With Cleft And Cleft Reparative Surgery On Overall Health And Speech Outcomes, Khatansuudal Evsanaa
The Impact Of Being Born With Cleft And Cleft Reparative Surgery On Overall Health And Speech Outcomes, Khatansuudal Evsanaa
Master's Theses
Orofacial cleft is one of the most common and treatable birth defects in the world. If left untreated, orofacial cleft can impair normal speech development, growth, and could lead to a number of health consequences later in life. The main motivation of the study is to measure the impact of being born with cleft and the cleft reparative surgery on overall speech and health cleft for teenagers in India using difference-in-differences approach along with household fixed effects method. An overall health outcome was measured using height, weight, grip strength and BMI, and the speech acceptability was measured using a “Universal …
A Dynamic-Trend Exponential Smoothing Model, Don Miller, Dan Williams
A Dynamic-Trend Exponential Smoothing Model, Don Miller, Dan Williams
Publications and Research
Forecasters often encounter situations in which the local pattern of a time series is not expected to persist over the forecasting horizon. Since exponential smoothing models emphasize recent behavior, their forecasts may not be appropriate over longer horizons. In this paper, we develop a new model in which the local trend line projected by exponential smoothing converges asymptotically to an assumed future long-run trend line, which might be an extension of a historical long-run trend line. The rapidity of convergence is governed by a parameter. A familiar example is an economic series exhibiting persistent long-run trend with cyclic variation. This …
Profile Likelihood Estimation Of Partially Linear Panel Data Models With Fixed Effects, Liangjun Su, Aman Ullah
Profile Likelihood Estimation Of Partially Linear Panel Data Models With Fixed Effects, Liangjun Su, Aman Ullah
Research Collection School Of Economics
We consider consistent estimation of partially linear panel data models with fixed effects. We propose profile-likelihood-based estimators for both the parametric and nonparametric components in the models and establish convergence rates and asymptotic normality for both estimators.
A Class Of Nonlinear Stochastic Volatility Models, Jun Yu, Zhenlin Yang
A Class Of Nonlinear Stochastic Volatility Models, Jun Yu, Zhenlin Yang
Research Collection School Of Economics
This paper proposes a class of nonlinear stochastic volatility models based on the Box-Cox transformation which offers an alternative to the one introduced in Andersen (1994). The proposed class encompasses many parametric stochastic volatility models that have appeared in the literature, including the well known lognormal stochastic volatility model, and has an advantage in the ease with which different specifications on stochastic volatility can be tested. In addition, the functional form of transformation which induces marginal normality of volatility is obtained as a byproduct of this general way of modeling stochastic volatility. The efficient method of moments approach is used …
Multivariate Stochastic Volatility Models: Bayesian Estimation And Model Comparison, Jun Yu, Renate Meyer
Multivariate Stochastic Volatility Models: Bayesian Estimation And Model Comparison, Jun Yu, Renate Meyer
Research Collection School Of Economics
In this paper we show that fully likelihood-based estimation and comparison of multivariate stochastic volatility (SV) models can be easily performed via a freely available Bayesian software called WinBUGS. Moreover, we introduce to the literature several new specifications which are natural extensions to certain existing models, one of which allows for time varying correlation coefficients. Ideas are illustrated by fitting, to a bivariate time series data of weekly exchange rates, nine multivariate SV models, including the specifications with Granger causality in volatility, time varying correlations, heavy-tailed error distributions, additive factor structure, and multiplicative factor structure. Empirical results suggest that the …
On Leverage In A Stochastic Volatility Model, Jun Yu
On Leverage In A Stochastic Volatility Model, Jun Yu
Research Collection School Of Economics
This paper is concerned with specification for modelling financial leverage effect in the context of stochastic volatility (SV) models. Two alternative specifications co-exist in the literature. One is the Euler approximation to the well known continuous time SV model with leverage effect and the other is the discrete time SV model of Jacquier, Polson and Rossi (2004, Journal of Econometrics, forthcoming). Using a Gaussian nonlinear state space form with uncorrelated measurement and transition errors, I show that it is easy to interpret the leverage effect in the conventional model whereas it is not clear how to obtain the leverage effect …
Deviance Information Criterion For Comparing Stochastic Volatility Models, Andreas Berg, Renate Meyer, Jun Yu
Deviance Information Criterion For Comparing Stochastic Volatility Models, Andreas Berg, Renate Meyer, Jun Yu
Research Collection School Of Economics
Bayesian methods have been efficient in estimating parameters of stochastic volatility models for analyzing financial time series. Recent advances made it possible to fit stochastic volatility models of increasing complexity, including covariates, leverage effects, jump components, and heavy-tailed distributions. However, a formal model comparison via Bayes factors remains difficult. The main objective of this article is to demonstrate that model selection is more easily performed using the deviance information criterion (DIC). It combines a Bayesian measure of fit with a measure of model complexity. We illustrate the performance of DIC in discriminating between various different stochastic volatility models using simulated …