Дисертації з теми "GMM, Panel Data Models"
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Cantarinha, Ana Isabel Guerra. "Comparação de estimadores alternativos para modelos dinâmicos com dados de painel." Master's thesis, Universidade de Évora, 2006. http://hdl.handle.net/10174/16338.
Повний текст джерелаHu, Wanhong. "Estimation of dynamic heterogeneous panel data models." Connect to resource, 1996. http://rave.ohiolink.edu/etdc/view.cgi?acc%5Fnum=osu1266934002.
Повний текст джерелаBada, Oualid [Verfasser]. "Essays on Large Panel Data Models / Oualid Bada." Bonn : Universitäts- und Landesbibliothek Bonn, 2015. http://d-nb.info/1077266820/34.
Повний текст джерелаMutl, Jan. "Dynamic panel data models with spatially correlated disturbances." College Park, Md. : University of Maryland, 2006. http://hdl.handle.net/1903/3729.
Повний текст джерелаThesis research directed by: Economics. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
Bun, Maurice Josephus Gerardus. "Accurate statistical analysis in dynamic panel data models." [Amsterdam : Amsterdam : Thela Thesis] ; Universiteit van Amsterdam [Host], 2001. http://dare.uva.nl/document/57690.
Повний текст джерелаSarafidis, Vasilis. "Estimating panel data models with cross-sectional dependence." Thesis, University of Cambridge, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.613908.
Повний текст джерелаKhatoon, Rabeya. "Estimation and inference of microeconometric models based on moment condition models." Thesis, University of Manchester, 2014. https://www.research.manchester.ac.uk/portal/en/theses/estimation-and-inference-of-microeconometric-models-based-on-moment-condition-models(fb572e1e-7238-4410-8e27-052b4a438962).html.
Повний текст джерелаMüller, Werner, and Michaela Nettekoven. "A Panel Data Analysis: Research & Development Spillover." Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 1998. http://epub.wu.ac.at/620/1/document.pdf.
Повний текст джерелаSeries: Forschungsberichte / Institut für Statistik
Shi, Wei. "Essays on Spatial Panel Data Models with Common Factors." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1461300292.
Повний текст джерелаPapa, Gianluca. "Essays on econometrics of panel data and treatment models." Doctoral thesis, Universite Libre de Bruxelles, 2013. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209408.
Повний текст джерелаThe first Chapter analyzes the investment behavior of a sample of R&D intensive firms which are quoted on the stock market from USA, UK and Japan for the period 1990-1998. By using an error correction model we test the elasticity of investment and R&D to cash flow in these countries to see by which measure different market institutions and corporate governance rules affects the cost of external financing. Contrary to previous studies, we find significant differences in the sensitivity to cash flow of the two types of investment, with R&D expenditure being much less sensitive than ordinary investment. This is not surprising given the more long-term nature of R&D expenditures. For what concerns the comparison between the different systems/countries, the USA stock markets confirms as the most efficient market providing outside financing at a much lower cost compared to other markets, especially for young, smaller firms.
The second Chapter is a joint work with Biagio Speciale. It uses the data on a panel of quoted UK firms over the period 1995–2002 to study the effects of financial leverage on managerial compensation. The change in the investors’ expectations that caused the recent collapse of the stock market tech bubble is a perfect example of natural experiment that has been used as a source of plausibly exogenous variation in the firm’s debt. The estimates show that pay-for-performance sensitivity is increasing in financial leverage, with the exception of the 10% most levered firms, giving rise at the end to a non-linear (inverted U-shape) relationship between the two variables. The chapter includes also a theoretical model accounting for this relationship where an higher leverage increases both the expected returns and the expected variance of investment returns: the first effect (determining increased pay-performance sensitivity) prevails for low leverage values and the second effect (determining decreased pay-performance sensitivity) prevails for high leverage values.
The third Chapter undertakes an empirical estimation of the additionality of public funding on both the propensity to initiate R&D activity and the intensity of R&D spending of Italian enterprises for the period 1998-2000, using data from the Third Community Innovation Survey and from firms' financial accounts. The chosen methodology (Endogenous Switching Type II-Tobit) takes into account the possibility that decisions about both starting an R&D activity (sample selection effect) and applying for/obtaining public funding (essential heterogeneity) are influenced by private knowledge of enterprises' idiosyncratic propensities in R&D spending. The present analysis shows that both these effects are indeed important and that they contribute to explain most of the additionality found with less sophisticated models.
The fourth Chapter investigates the underlying causes of variability of public health expenditure per capita (SSPC henceforth) between Italian regions. A fixed-effect panel data estimate on the SSPC (for the period 1997-2006) is used in the first part of the paper to account for regional differences in terms of physical, demographic, socio-economic characteristics and in terms of other variables that affect demand and supply of health services. In the second part, we take the ‘adjusted’ SSPC and proceed to estimate an "efficient production function" of the quality of health services through Data Envelopment Analysis. This procedure allows us to separate the share of expenditure used for the improvement of the quality from the one that can be traced only to an inefficient use of financial resources. A comparison of regional SSPC after factoring out the socio-economic factors and the quality of healthcare shows that big differences still remain and are even exacerbated, signalling big pockets of inefficiency and correspondingly a huge potential for cost savings. Finally, a preliminary analysis shows a positive correlation between the efficiency of regional public spending in healthcare and the level of social capital.
Doctorat en Sciences économiques et de gestion
info:eu-repo/semantics/nonPublished
Loudermilk, Margaret Susan. "Estimation and testing in dynamic, nonlinear panel data models." Diss., Connect to online resource - MSU authorized users, 2006.
Знайти повний текст джерелаEvaldsson, Matilda. "Has EMU Led to Higher Debt Levels? : -A Dynamic Panel Data Estimation." Thesis, KTH, Industriell ekonomi och organisation (Inst.), 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-120396.
Повний текст джерелаCiccarelli, Matteo. "Bayesian interference in heterogeneous dynamic panel data models: three essays." Doctoral thesis, Universitat Pompeu Fabra, 2001. http://hdl.handle.net/10803/31792.
Повний текст джерелаWinther, Blindum Steen. "Strict exogeneity and nonlinear panel data models with unobserved heterogeneity /." Copenhagen, 2005. http://www.gbv.de/dms/zbw/50660389X.pdf.
Повний текст джерелаArellano, Gomez Manuel. "Estimation and testing of dynamic econometric models from panel data." Thesis, London School of Economics and Political Science (University of London), 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.261293.
Повний текст джерелаLee, Joonhwan, and Iván Fernández-Val. "Panel data models with nonadditive unobserved heterogeneity : estimation and inference." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/87526.
Повний текст джерела"February 2014." Abstract page contains the following information: "This paper is based in part on the second chapter of Fernández-Val (2005)'s MIT PhD dissertation." -- Authors: "Iván Fernández-Val and Joonhwan Lee." Cataloged from PDF version of thesis.
Includes bibliographical references (pages 25-27 (first group)).
This paper considers fixed effects estimation and inference in linear and nonlinear panel data models with random coefficients and endogenous regressors. The quantities of interest - means, variances, and other moments of the random coefficients - are estimated by cross sectional sample moments of GMM estimators applied separately to the time series of each individual. To deal with the incidental parameter problem introduced by the noise of the within-individual estimators in short panels, we develop bias corrections. These corrections are based on higher-order asymptotic expansions of the GMM estimators and produce improved point and interval estimates in moderately long panels. Under asymptotic sequences where the cross sectional and time series dimensions of the panel pass to infinity at the same rate, the uncorrected estimator has an asymptotic bias of the same order as the asymptotic variance. The bias corrections remove the bias without increasing variance. An empirical example on cigarette demand based on Becker, Grossman and Murphy (1994) shows significant heterogeneity in the price effect across U.S. states.
by Joonhwan Lee.
S.M.
Zhang, Miao. "The comparison of stochastic frontier analysis with panel data models." Thesis, Loughborough University, 2012. https://dspace.lboro.ac.uk/2134/9643.
Повний текст джерелаMuller, Christoffel Joseph Brand. "Bayesian approaches of Markov models embedded in unbalanced panel data." Thesis, Stellenbosch : Stellenbosch University, 2012. http://hdl.handle.net/10019.1/71910.
Повний текст джерелаENGLISH ABSTRACT: Multi-state models are used in this dissertation to model panel data, also known as longitudinal or cross-sectional time-series data. These are data sets which include units that are observed across two or more points in time. These models have been used extensively in medical studies where the disease states of patients are recorded over time. A theoretical overview of the current multi-state Markov models when applied to panel data is presented and based on this theory, a simulation procedure is developed to generate panel data sets for given Markov models. Through the use of this procedure a simulation study is undertaken to investigate the properties of the standard likelihood approach when fitting Markov models and then to assess its shortcomings. One of the main shortcomings highlighted by the simulation study, is the unstable estimates obtained by the standard likelihood models, especially when fitted to small data sets. A Bayesian approach is introduced to develop multi-state models that can overcome these unstable estimates by incorporating prior knowledge into the modelling process. Two Bayesian techniques are developed and presented, and their properties are assessed through the use of extensive simulation studies. Firstly, Bayesian multi-state models are developed by specifying prior distributions for the transition rates, constructing a likelihood using standard Markov theory and then obtaining the posterior distributions of the transition rates. A selected few priors are used in these models. Secondly, Bayesian multi-state imputation techniques are presented that make use of suitable prior information to impute missing observations in the panel data sets. Once imputed, standard likelihood-based Markov models are fitted to the imputed data sets to estimate the transition rates. Two different Bayesian imputation techniques are presented. The first approach makes use of the Dirichlet distribution and imputes the unknown states at all time points with missing observations. The second approach uses a Dirichlet process to estimate the time at which a transition occurred between two known observations and then a state is imputed at that estimated transition time. The simulation studies show that these Bayesian methods resulted in more stable results, even when small samples are available.
AFRIKAANSE OPSOMMING: Meerstadium-modelle word in hierdie verhandeling gebruik om paneeldata, ook bekend as longitudinale of deursnee tydreeksdata, te modelleer. Hierdie is datastelle wat eenhede insluit wat oor twee of meer punte in tyd waargeneem word. Hierdie tipe modelle word dikwels in mediese studies gebruik indien verskillende stadiums van ’n siekte oor tyd waargeneem word. ’n Teoretiese oorsig van die huidige meerstadium Markov-modelle toegepas op paneeldata word gegee. Gebaseer op hierdie teorie word ’n simulasieprosedure ontwikkel om paneeldatastelle te simuleer vir gegewe Markov-modelle. Hierdie prosedure word dan gebruik in ’n simulasiestudie om die eienskappe van die standaard aanneemlikheidsbenadering tot die pas vanMarkov modelle te ondersoek en dan enige tekortkominge hieruit te beoordeel. Een van die hoof tekortkominge wat uitgewys word deur die simulasiestudie, is die onstabiele beramings wat verkry word indien dit gepas word op veral klein datastelle. ’n Bayes-benadering tot die modellering van meerstadiumpaneeldata word ontwikkel omhierdie onstabiliteit te oorkom deur a priori-inligting in die modelleringsproses te inkorporeer. Twee Bayes-tegnieke word ontwikkel en aangebied, en hulle eienskappe word ondersoek deur ’n omvattende simulasiestudie. Eerstens word Bayes-meerstadium-modelle ontwikkel deur a priori-verdelings vir die oorgangskoerse te spesifiseer en dan die aanneemlikheidsfunksie te konstrueer deur van standaard Markov-teorie gebruik te maak en die a posteriori-verdelings van die oorgangskoerse te bepaal. ’n Gekose aantal a priori-verdelings word gebruik in hierdie modelle. Tweedens word Bayesmeerstadium invul tegnieke voorgestel wat gebruik maak van a priori-inligting om ontbrekende waardes in die paneeldatastelle in te vul of te imputeer. Nadat die waardes ge-imputeer is, word standaard Markov-modelle gepas op die ge-imputeerde datastel om die oorgangskoerse te beraam. Twee verskillende Bayes-meerstadium imputasie tegnieke word bespreek. Die eerste tegniek maak gebruik van ’n Dirichletverdeling om die ontbrekende stadium te imputeer by alle tydspunte met ’n ontbrekende waarneming. Die tweede benadering gebruik ’n Dirichlet-proses om die oorgangstyd tussen twee waarnemings te beraam en dan die ontbrekende stadium te imputeer op daardie beraamde oorgangstyd. Die simulasiestudies toon dat die Bayes-metodes resultate oplewer wat meer stabiel is, selfs wanneer klein datastelle beskikbaar is.
Zhang, Yonghui. "Three essays on large panel data models with cross-sectional dependence." Thesis, Singapore Management University (Singapore), 2013. http://pqdtopen.proquest.com/#viewpdf?dispub=3601351.
Повний текст джерелаMy dissertation consists of three essays which contribute new theoretical results to large panel data models with cross-sectional dependence. These essays try to answer or partially answer some prominent questions such as how to detect the presence of cross-sectional dependence and how to capture the latent structure of cross-sectional dependence and estimate parameters efficiently by removing its effects.
Chapter 2 introduces a nonparametric test for cross-sectional contemporaneous dependence in large dimensional panel data models based on the squared distance between the pair-wise joint density and the product of the marginals. The test can be applied to either raw observable data or residuals from local polynomial time series regressions for each individual to estimate the joint and marginal probability density functions of the error terms. In either case, we establish the asymptotic normality of our test statistic under the null hypothesis by permitting both the cross section dimension n and the time series dimension T to pass to infinity simultaneously and relying upon the Hoeffding decomposition of a two-fold U-statistic. We also establish the consistency of our test. A small set of Monte Carlo simulations is conducted to evaluate the finite sample performance of our test and compare it with that of Pesaran (2004) and Chen, Gao, and Li (2009).
Chapter 3 analyzes nonparametric dynamic panel data models with interactive fixed effects, where the predetermined regressors enter the models nonparametrically and the common factors enter the models linearly but with individual specific factor loadings. We consider the issues of estimation and specification testing when both the cross-sectional dimension N and the time dimension T are large. We propose sieve estimation for the nonparametric function by extending Bai's (2009) principal component analysis (PCA) to our nonparametric framework. Following Moon and Weidner's (2010, 2012) asymptotic expansion of the Gaussian quasilog-likelihood function, we derive the convergence rate for the sieve estimator and establish its asymptotic normality. The sources of asymptotic biases are discussed and a consistent bias-corrected estimator is provided. We also propose a consistent specification test for the linearity of the nonparametric functional form by comparing the linear and sieve estimators. We establish the asymptotic distributions of the test statistic under both the null hypothesis and a sequence of Pitman local alternatives.
To improve the finite sample performance of the test, we also propose a bootstrap procedure to obtain the bootstrap p-values and justify its validity. Monte Carlo simulations are conducted to investigate the finite sample performance of our estimator and test. We apply our model to an economic growth data set to study the relationship between capital accumulation and real GDP growth rate.
Chapter 4 proposes a nonparametric test for common trends in semiparametric panel data models with fixed effects based on a measure of nonparametric goodness-of-fit (R2). We first estimate the model under the null hypothesis of common trends by the method of profile least squares, and obtain the augmented residual which consistently estimates the sum of the fixed effect and the disturbance under the null.
Then we run a local linear regression of the augmented residuals on a time trend and calculate the nonparametric R2 for each cross section unit. The proposed test statistic is obtained by averaging all cross sectional nonparametric R2's, which is close to 0 under the null and deviates from 0 under the alternative. We show that after appropriate standardization the test statistic is asymptotically normally distributed under both the null hypothesis and a sequence of Pitman local alternatives. We prove test consistency and propose a bootstrap procedure to obtain p-values. Monte Carlo simulations indicate that the test performs well infinite samples. Empirical applications are conducted exploring the commonality of spatial trends in UK climate change data and idiosyncratic trends in OECD real GDP growth data. Both applications reveal the fragility of the widely adopted common trends assumption.
Fernández-Val, Iván. "Three essays on nonlinear panel data models and quantile regression analysis." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/32408.
Повний текст джерелаIncludes bibliographical references.
This dissertation is a collection of three independent essays in theoretical and applied econometrics, organized in the form of three chapters. In the first two chapters, I investigate the properties of parametric and semiparametric fixed effects estimators for nonlinear panel data models. The first chapter focuses on fixed effects maximum likelihood estimators for binary choice models, such as probit, logit, and linear probability model. These models are widely used in economics to analyze decisions such as labor force participation, union membership, migration, purchase of durable goods, marital status, or fertility. The second chapter looks at generalized method of moments estimation in panel data models with individual-specific parameters. An important example of these models is a random coefficients linear model with endogenous regressors. The third chapter (co-authored with Joshua Angrist and Victor Chernozhukov) studies the interpretation of quantile regression estimators when the linear model for the underlying conditional quantile function is possibly misspecified.
by Iván Fernández-Val.
Ph.D.
Iwakura, Haruo. "Asymptotic Efficiency of Estimates for Panel Data Models with Fixed Effect." Kyoto University, 2014. http://hdl.handle.net/2433/188444.
Повний текст джерелаHumphreys, Keith. "Latent variable models for discrete longitudinal data with measurement error." Thesis, University of Southampton, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.295045.
Повний текст джерелаKleiber, Christian, and Achim Zeileis. "The Grunfeld Data at 50." Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 2008. http://epub.wu.ac.at/464/1/document.pdf.
Повний текст джерелаSeries: Research Report Series / Department of Statistics and Mathematics
Lo, Chi-ho, and 盧子豪. "Estimation of structural parameters for panel data in credibility context." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2005. http://hub.hku.hk/bib/B31557442.
Повний текст джерелаKazemi, Iraj. "The initial conditions problem in dynamic panel data models with random effects." Thesis, Lancaster University, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.431463.
Повний текст джерелаAbrevaya, Jason. "Semiparametric estimation methods for nonlinear panel data models and mismeasured dependent variables." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/10822.
Повний текст джерелаHoonhout, P. J. M. "Identification and estimation of panel data models with attrition using refreshment samples." Thesis, University College London (University of London), 2011. http://discovery.ucl.ac.uk/1318085/.
Повний текст джерелаAfonso, Lutcy Menezes. "Correcting for attrition in panel data using inverse probability weighting : an application to the european bank system." Master's thesis, Instituto Superior de Economia e Gestão, 2015. http://hdl.handle.net/10400.5/8155.
Повний текст джерелаEsta dissertação analiza técnicas de correção do efeito do enviesamento que pode ocorrer no caso dos dados utilizados apresentarem valores em falta. Tais técnicas serão aplicadas a um modelo económico para caracterização da margem líquida de juros (MLJ) bancária, utilizando dados provinientes 15 países que pertencem ao sistema bancário da União Europeia (UE15). As variáveis que caracterizam os bancos são observados entre de 2004 e 2010. E são escolhidas seguindo Valverde et al. (2007). Adicionalmente aos regressores são acrescentadas algumas variáveis macroeconómicas. A seleção proviniente da falta de alguns valores para os regressores é tratada através da ponderação probabilistica inversa. Os ponderadores são aplicados a estimadores GMM para um modelo de dados de painel dinámico.
This thesis discusses techniques to correct for the potentially biasing effects of missing data. We apply the techniques on an economic model that explains the Net Interest margin (NIM) of banks, using data from 15 countries that are part of the European Union (EU15) banking system. The variables that describe banks cover the period 2004 and 2010. We use the variables that were also used in Carbó-Valverde and Fernndez (2007). In addition, also macroeconomic variables are used as regressors. The selection that occurs as a consequence of missing values in these regressor variables is dealt with by means of Inverse Probability Weighting (IPW) techniques. The weights are applied to a GMM estimator for a dynamic panel data model that would have been consistent in the absence of missing data.
Badinger, Harald, and Peter Egger. "Estimation and Testing of Higher-Order Spatial Autoregressive Panel Data Error Component Models." Springer, 2013. http://epub.wu.ac.at/5468/1/JoGS_2012.pdf.
Повний текст джерелаAkinc, Deniz. "Statistical Modelling Of Financial Statements Of Turkey: A Panel Data Analysis." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/2/12609824/index.pdf.
Повний текст джерелаs Turkey, the statistical methods that are used for this purpose involve single level models applied to cross-sectional data. However, multilevel models applied to panel data are more preferable as they gather more information, and also, enable the calculated financial success probabilities to be more trustworthy. In this thesis, publicly available panel data that are collected from The Istanbul Stock Exchange are investigated. Mainly, financial success of companies from two sectors, namely industry and services, are investigated. For the analysis of this panel data, data exploration methods, missing data imputation, possible solutions to multicollinearity problem, single level logistic regression models and multilevel models are used. By these models, financial success probabilities for each company are calculated
the factors related to the financial failure are determined, and changes in time are observed. Models and early warning systems resulted in correct classification rates of up to 100%. In the services sector, a small number of companies having publicly available data result in a decline in the success of models. It is concluded that sharing data with more subjects observed in a longer time period collected in the same format with academicians, will result in better justified outputs, which are useful for both academicians and managers.
Ranganathan, Shyam. "Non-linear dynamic modelling for panel data in the social sciences." Doctoral thesis, Uppsala universitet, Tillämpad matematik och statistik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-261289.
Повний текст джерелаLundmark, Albin, and Emma Roxström. "Urbanization and economic freedom - are they threats to air quality? : Evidence from a panel study of low and lower-middle-income countries." Thesis, Uppsala universitet, Nationalekonomiska institutionen, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-435088.
Повний текст джерелаRodrigues, Paulo Jorge Maurício. "Panel data models with spatially correlated and heteroscedastic innovations : large and small sample results /." [S.l. : s.n.], 2007. http://swbplus.bsz-bw.de/bsz277731119inh.pdf.
Повний текст джерелаSalabasis, Mickael. "Bayesian time series and panel models : unit roots, dynamics and random effects." Doctoral thesis, Stockholm : Economic Research Institute, Stockholm School of Economics (Ekonomiska forskningsinstitutet vid Handelshögsk.) (EFI), 2004. http://www.hhs.se/efi/summary/632.htm.
Повний текст джерелаDarpeix, Pierre-Emmanuel. "Three essays in applied economics with panel data." Thesis, Paris Sciences et Lettres (ComUE), 2018. http://www.theses.fr/2018PSLEH099/document.
Повний текст джерелаThis dissertation is composed of three empirical articles resorting to econometric methods in panel data analysis to address various research questions. The main article investigates the evolution of the level of price transmission for the three major cereals (wheat, maize and rice) from the international commodity markets down to the local producers for 52 countries between 1970 and 2013 while attempting to identify the main drivers of the heterogeneity in pass-through. The second article measures the elasticity of air-traffic to GDP around the world and demonstrates that the relationship is very stable across régions and through time. Eventually, the third article models the mechanisms through which French life-insurers set the rate of return they pay annually to their policyholders
LeSage, James P., and Manfred M. Fischer. "Conventional versus network dependence panel data gravity model specifications." WU Vienna University of Economics and Business, 2019. http://epub.wu.ac.at/6828/1/2019%2D2%2D11_v12_panel_gravity_model.pdf.
Повний текст джерелаSeries: Working Papers in Regional Science
Collado-Vindel, Maria Dolores. "Dynamic econometric models for cohort and panel data : methods and applications to life-cycle consumption." Thesis, London School of Economics and Political Science (University of London), 1994. http://etheses.lse.ac.uk/2829/.
Повний текст джерелаSalish, Nazarii [Verfasser]. "Essays on Heterogeneity and Non-Linearity in Panel Data and Time Series Models / Nazarii Salish." Bonn : Universitäts- und Landesbibliothek Bonn, 2016. http://d-nb.info/1188703617/34.
Повний текст джерелаSandberg, Rickard. "Testing the unit root hypothesis in nonlinear time series and panel models." Doctoral thesis, Handelshögskolan i Stockholm, Ekonomisk Statistik (ES), 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:hhs:diva-536.
Повний текст джерелаDiss. Stockholm : Handelshögskolan, 2004
Kessler, Lawrence. "Bayesian Estimation of Panel Data Fractional Response Models with Endogeneity: An Application to Standardized Test Rates." Scholar Commons, 2013. http://scholarcommons.usf.edu/etd/4518.
Повний текст джерелаStammann, Amrei [Verfasser], Florian [Gutachter] Heiß, and Joel [Gutachter] Stiebale. "Nonlinear Panel Data Models with High-Dimensional Fixed Effects / Amrei Stammann ; Gutachter: Florian Heiß, Joel Stiebale." Düsseldorf : Universitäts- und Landesbibliothek der Heinrich-Heine-Universität Düsseldorf, 2020. http://d-nb.info/1203369735/34.
Повний текст джерелаFeng, Qu. "Essays on testing for cross-sectional dependence and estimation of change points in panel data models." Related electronic resource: Current Research at SU : database of SU dissertations, recent titles available full text, 2009. http://wwwlib.umi.com/cr/syr/main.
Повний текст джерелаLeSage, James P., and Manfred M. Fischer. "MCMC estimation of panel gravity models in the presence of network dependence." WU Vienna University of Economics and Business, 2018. http://epub.wu.ac.at/6550/1/2018%2D10%2D2_WU%2DPub__panel_gravity_model.pdf.
Повний текст джерелаSeries: Working Papers in Regional Science
LeSage, James, and Manfred M. Fischer. "Cross-sectional dependence model specifications in a static trade panel data setting." WU Vienna University of Economics and Business, 2019. http://epub.wu.ac.at/6886/1/2019%2D03%2D31_WP_Cross%2Dsectional.pdf.
Повний текст джерелаSeries: Working Papers in Regional Science
LeSage, James P., and Manfred M. Fischer. "Cross-sectional dependence model specifications in a static trade panel data setting." WU Vienna University of Economics and Business, 2017. http://epub.wu.ac.at/5904/1/intl_trade_flows_dec_07_2017v3.pdf.
Повний текст джерелаSeries: Working Papers in Regional Science
Ruzibuka, John S. "The impact of fiscal deficits on economic growth in developing countries : Empirical evidence and policy implications." Thesis, University of Bradford, 2012. http://hdl.handle.net/10454/16282.
Повний текст джерелаKapoor, Mudit. "Panel data models with spatial correlation estimation theory and empirical investigation of the US wholesale gasoline industry /." College Park, Md. : University of Maryland, 2003. http://hdl.handle.net/1903/143.
Повний текст джерелаThesis research directed by: Economics. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
Pihl, Svante, and Leonardo Olivetti. "An Empirical Comparison of Static Count Panel Data Models: the Case of Vehicle Fires in Stockholm County." Thesis, Uppsala universitet, Statistiska institutionen, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-412014.
Повний текст джерелаTekieh, Mohammad Hossein. "Analysis of Healthcare Coverage Using Data Mining Techniques." Thèse, Université d'Ottawa / University of Ottawa, 2012. http://hdl.handle.net/10393/20547.
Повний текст джерелаRuzibuka, John Shofel. "The impact of fiscal deficits on economic growth in developing countries : empirical evidence and policy implications." Thesis, University of Bradford, 2012. http://hdl.handle.net/10454/16282.
Повний текст джерела