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Hansen, Elizabeth Ann. "Penalized likelihood estimation of a fixed-effect and a mixed-effect transfer function model." Diss., University of Iowa, 2006. http://ir.uiowa.edu/etd/58.
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Náglová, Zdeňka. "Podpory potravinářského sektoru ČR v kontextu s fondy EU a jejich dopady." Doctoral thesis, Česká zemědělská univerzita v Praze, 2016. http://www.nusl.cz/ntk/nusl-259705.
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Dissertation deals with the food industry. First, the economy of the sector in the branch structure and size of businesses is evaluated. The main attention is paid to the drawing subsidies by the food industry in the context of EU funds. The main objective of this thesis is to evaluate the effect of the subsidies on the economy of the food business. For the analysis fixed effect model was used. According to the results, there are significant differences in the impact of subsidies on the individual branches of the food industry. In most fields was demonstrated their ineffective use to increase business performance.
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Rasch, Dieter, Thomas Rusch, Marie Simeckova, Klaus D. Kubinger, Karl Moder, and Petr Simecek. "Tests of additivity in mixed and fixed effect two-way ANOVA models with single sub-class numbers." Springer, 2009. http://dx.doi.org/10.1070/s00362-009-0254-4.
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In variety testing as well as in psychological assessment, the situation occurs that in a
two-way ANOVA-type model with only one replication per cell, analysis is done under
the assumption of no interaction between the two factors. Tests for this situation are
known only for fixed factors and normally distributed outcomes. In the following we will
present five additivity tests and apply them to fixed and mixed models and to quantitative
as well as to Bernoulli distributed data. We consider their performance via simulation
studies with respect to the type-I-risk and power. Furthermore, two new approaches
will be presented, one being a modification of Tukey's test and the other being a new
experimental design to test for interactions.
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Frey, Reik. "International and domestic Migration Patterns : International immigration effect on internal out-migration patterns in the German states between 1993 and 2016." Thesis, Internationella Handelshögskolan, Högskolan i Jönköping, IHH, Nationalekonomi, 1994. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-44226.
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Internal migration has frequently been subject of empirical research. This study attempts to find a relationship between international immigration and internal out-migration in all German states, covering the time period between 1993 and 2016. The underlying theories were established by Card et al. (2008), Schlömer (2012), Florida (2002) and Chiswick and Miller (2015). These were used to develop a modified version of the gravity model. The dataset was received from the Federal Statistical Office of Germany (Statistisches Bundesamt). The regressions were executed using a fixed effects model and a pooled OLS as a robustness check. The empirical findings suggest no evidence of a statistically significant effect of international immigration on internal out-migration patterns in the covered period. Control variables suggest policymakers to focus on other factors when the effects of immigration policies on internal out-migration are being considered.
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HE, Ran. "Carry-over and interaction effects of different hand-milking techniques and milkers on milk." Thesis, Uppsala universitet, Statistiska institutionen, 1986. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-154641.
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The main idea of this thesis is studying the importance of the carry-over effects and interaction effects in statistical models. To investigate it, a hand-milking experiment in Burkina Faso was studied. In many no electricity access countries, such as Burkina Faso, the amount of milk and milk compositions are still highly relying on hand-milking techniques and milkers. Moreover, the time effects also plays a important role in stockbreeding system. Therefore, falling all effects, carry-over effects and interaction effects into a linear mixed effects model, it is concluded that the carry-over effects of milker and hand-milking techniques cannot be neglected, and the interaction effects among hand-milking techniques, different milkers, days and periods can be substantial.
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Maengando, Angshed Sara, and Fluck Vendela von. "An analysis of the determinants of Foreign Direct Investments to OECD countries." Thesis, Södertörns högskola, Nationalekonomi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:sh:diva-38247.
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This study examines the determinants of inward foreign direct investment to OECD countries. The focus is on horizontal FDI. The purpose of the research is to contribute to the ongoing research, and adding value. This is done by using a dynamic perspective of time, and controlling for country-specific characteristics. The thesis uses panel data covering all 36 OECD countries over a 23 year long time period, 1995-2017. Three regressions have been done using a linear fixed effects model, as well as four addition regressions testing the robustness of the results. Earlier studies have received spread results, as have this study. It found market size, economic stability, trade openness, and currency value as significant determinants of the inward flow of FDI to OECD countries.
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Mingolini, Riccardo. "Investimenti in lobby: Un modello per stimare il loro impatto sull'azienda." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2017. http://amslaurea.unibo.it/13291/.
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In questo elaborato di tesi verrà analizzata l’attitudine di una azienda ad investire in lobbying, misurato attraverso varie variabili importanti per la stessa quali ad esempio il capitale, il reddito netto dell’impresa, il numero degli impiegati (et simila) e il loro impatto scoraggiante o incentivante rispetto alla nostra variabile dipendente.
Cercheremo infine di trovare un modello che approssima in modo sostanziale suddette dipendenze e variabili, in modo da tracciare un filo logico e matematico fra la nostra variabile dipendente Y ( investimento in lobbying) e le nostre variabili indipendenti X cioè gli indici e le variabili in valore monetario importanti per definire una azienda e il suo settore di appartenenza (SIC CODE).
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Kamangar, Daniel, and Richard Sundin. "Management and CEO Stock Ownership and its Effect on Company Performance." Thesis, KTH, Matematisk statistik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-229670.
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This is a study on the effect of management and CEO stock ownership on company performance. A regression analysis is performed on panel data consisting of a sample of 30 companies listed on OMX Stockholm Mid Cap. A total of 210 and 2520 observations is considered on a yearly and monthly basis, respectively, for seven years (2010-2016). The Hausman test is applied for determining between the fixed effects and random effects regression models. Results show that management relative stock ownership has a significant positive effect on company net income growth and return on assets. The effect is not significant for CEO stock ownership, which is contrary to what commonly has been shown for large companies in previous research. Moreover, alternative methodology is discussed for the benefit of the future researcher. The authors illustrate how the selection of dummy variables can be vital for final model outcomes, and it is thus an important aspect to consider when performing panel data analysis.I den här studien undersöks hur aktieinnehav hos ledning och den verkställande direktören i ett företag påverkar företagsutvecklingen. Studien genomförs med regressionsanalys på paneldata som består av 30 företag, samtliga noterade på OMX Stockholm Mid Cap. Totalt samlas 210 och 2520 observationer på årsbasis respektive månadsbasis över sju år (2010-2016). Hausman-testet används för att bestämma vilken av fixed effects-modellen och random effects-modellen som ska användas i regressionen. Resultaten visar att relativt aktieinnehav hos ledningen har en positiv signifikant påverkan på ett företags nettoinkomstutveckling och avkastning på tillgångar. Den verkställande direktörens aktieinnehav visas inte vara signifikant, vilket är motsatt till det som generellt har visats för stora företag i tidigare forskning. Regressionerna genomförs även med alternativa metoder, vilka det resoneras kring i en diskussion som bör vara till gagn för vidare forskning. Författarna illustrerar hur val av dummy-variabler kan ha en avgörande betydelse för regressionsanalysen, och att det således är en viktig aspekt att ta hänsyn till när regressioner genomförs på paneldata.
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Petrovic, Katarina. "Government Debt : Why Has the Government Debt Increased? An Analysis of What Factors Influence the Long-Term Interest Rate?" Thesis, Karlstads universitet, Fakulteten för ekonomi, kommunikation och IT, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-29051.
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This paper analyzes what factors influence the long-term interest rate, in order to give an understanding of why the government debt has increased in EU member states. It is a statistical study of panel data analyzed by the fixed effect model. The research of the 27 EU member states is based on secondary data from the European Commission; Eurostat and EconStats. The results by the fixed effect model show that government debt, budget deficit and presidential system are significant and have a positive relationship with the long- term interest rate. The growth rate is significant, having a negative relationship with the long-term interest rate and the financial crisis did not increase the long-term interest rate. The results were not entirely consistent with theories and previous studies.
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Schanzer-Larsen, Arnold. "The effects of immigration on the income of native born workers: Evidence from Sweden." Thesis, Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-54685.
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Abstract Course: NAA305 Bachelor Thesis in Economics 15 ECTS University: Mälardalen University, School of Business, Society and Engineering, Västerås Title: The effects of immigration on the income of native-born workers: Evidence from Sweden Author: Arnold Schanzer-Larsen Supervisor: Johan Lindén Problem: Sweden has experienced a lot of immigration, and the phenomenon has received a great deal of attention in the public and political debate. There is, among other things, fear that immigration could be harmful for the labor market outcome of the receiving country. Researchers from a variety of countries have tried to address this issue by estimating the effect of immigration on the native wage of the receiving country. The results have varied strongly and no universal conclusion can be drawn. For what can be said about Sweden, there is no paper (of our knowledge) that has done any similar estimates. For that reason, it is of great importance that there is some research which could bring empirical evidence and shed light on the debate. Purpose of the Research: The aim of the thesis is to quantitatively measure immigrations effect on the wage of native workers in Sweden. Methodology: Conducting a panel study, observation of the average native income from 290 municipalities over 2011-2019 was collected. The effect was estimated using OLS regression technique and a fixed effect model. Conclusion: From a 10% increase in the share of foreign-born within a municipality, led on average to a 2.89% increase in the native average income in that municipality. Keywords: Immigration, Income, Wage, Unemployment rate, Panel study, Fixed effect model, Native, Labor market, The equilibrium model, Human capital, Skill-composition
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Wickström, David. "Dawn of the radicals : The connection between economic growth and political radicalism." Thesis, Linnéuniversitetet, Institutionen för nationalekonomi och statistik (NS), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-47340.
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This thesis explores how economic performance, measured as real GDP-growth per capita, affects the vote share of parties which relies on radical ideological platforms. Using a fixed effect model with panel data, based on real electoral outcomes of 18 western European democracies, the result reveals an ambiguous reality. The overall conclusion implies that low growth rates benefit the electoral success of radical-right parties and holds for robustness checks. No solid evidence of the relationship is found on the radical-left side.The result further reveals that the individuals decision to vote radical is relative more affected by the ongoing business cycle trend between the elections rather than sudden changes close to the election day. The relationship also appears to be stronger among nations of southern Europe.
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Li, Guangjie. "Essays on economic and econometric applications of Bayesian estimation and model comparison." Thesis, University of Leicester, 2009. http://hdl.handle.net/2381/4792.
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This thesis consists of three chapters on economic and econometric applications of Bayesian parameter estimation and model comparison. The first two chapters study the incidental parameter problem mainly under a linear autoregressive (AR) panel data model with fixed effect. The first chapter investigates the problem from a model comparison perspective. The major finding in the first chapter is that consistency in parameter estimation and model selection are interrelated. The reparameterization of the fixed effect parameter proposed by Lancaster (2002) may not provide a valid solution to the incidental parameter problem if the wrong set of exogenous regressors are included. To estimate the model consistently and to measure its goodness of fit, the Bayes factor is found to be more preferable for model comparson than the Bayesian information criterion based on the biased maximum likelihood estimates. When the model uncertainty is substantial, Bayesian model averaging is recommended. The method is applied to study the relationship between financial development and economic growth. The second chapter proposes a correction function approach to solve the incidental parameter problem. It is discovered that the correction function exists for the linear AR panel model of order p when the model is stationary with strictly exogenous regressors. MCMC algorithms are developed for parameter estimation and to calculate the Bayes factor for model comparison. The last chapter studies how stock return's predictability and model uncertainty affect a rational buy-and-hold investor's decision to allocate her wealth for different lengths of investment horizons in the UK market. The FTSE All-Share Index is treated as the risky asset, and the UK Treasury bill as the riskless asset in forming the investor's portfolio. Bayesian methods are employed to identify the most powerful predictors by accounting for model uncertainty. It is found that though stock return predictability is weak, it can still affect the investor's optimal portfolio decisions over different investment horizons.
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Cau, Nicklasson Ronnie, and Simon Hansson. "Investment Companies’ Discount Fluctuation on the Swedish Market : A statistical analysis regarding different micro- and macroeconomic factors influence on Swedish closed-end funds’ discount." Thesis, Internationella Handelshögskolan, Högskolan i Jönköping, IHH, Economics, Finance and Statistics, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-21250.
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Closed-end funds’ (CEF) discount and discount fluctuations have been puzzling researchers for decades. Up to date, there are no multidimensional or cross-sectional variables that have been proved to influence CEFs simultaneously. Fact is that, earlier research and theories on the subject are contradictious and several suggestions on the origin of the CEF’s discount and its fluctuations have been proposed. To mention a few, investor sentiments, taxation issues, dividend policies, agency costs and agency problems are considered to influence these discounts. The purpose of this report is to examine the relationship between micro- and macroeconomic variables fluctuations, and how these can explain the discount fluctuation of the Swedish CEFs. This report focuses upon the CEFs traded at NASDAQ OMX Stockholm, which have been selected through a comprehensive multistage selection process. 10 CEFs were selected. Monthly data for calculating micro- and macroeconomic variables was collected for the period March 2003 – February 2013, which resulted in approximately 1 200 observations. OLS regression analysis, Fixed- and Random Effect Models and Hausman tests were conducted. The findings conclude that some of this report’s chosen micro- and macro variables influence on the Swedish CEFs’ discount fluctuation, although these findings are conditioned. The CEFs’ individual characteristics or traits result in a significant impact on the fluctuation of CEFs’ discount. Hence, only by controlling these characteristics, multidimensional or cross-sectional micro- and macroeconomic variables can be proved to affect the CEFs’ discount fluctuation.
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Persson, Sanna, and Jerry Pettersson. "The connection between household savings ratio and human development index : Which factors affect the household savings ratio?" Thesis, Linnéuniversitetet, Institutionen för ekonomistyrning och logistik (ELO), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-87939.
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This thesis investigates which factors affecting savings behavior by using a fixed effect regression model. To see what affects the household savings rate the following independent variables is considered: Natural logarithm of trend per capita income, natural logarithm of deviation from trend per capita income, growth of disposable income, real interest rate, inflation, wealth in relation to household disposable income, foreign savings in relation to disposable income, dependency ratio and human development index. To see whether changes of human development within a county impacts the household´s savings ratio this variables was included in a separate regression. To avoid possible biasedness from ordinary least square, a panel data technique called fixed effect regression model is used. The investigated time period is between year 1999 and 2016 and to make a restriction, variables from 25 developed countries were studied. The involved economic theories in this work are Keynesianism, permanent income hypothesis and the savings theory behind Maslow´s behavioral pyramid. The result made by using this study is that growth in income and foreign savings in relation to disposable income is insignificant and can´t be used in explaining the differences between household´s savings. Human development index within a country has a negative effect on the savings ratio but a conclusion regarding whether changes in HDI´s does affect savings can´t be made and more research within that field is needed.
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Silva, Thandara Maria Kathleen da. "O impacto do "Minha Casa Minha Vida" nas eleições presidenciais no Brasil." Universidade Federal de Juiz de Fora (UFJF), 2018. https://repositorio.ufjf.br/jspui/handle/ufjf/7185.
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O objetivo deste trabalho é analisar o retorno eleitoral do Programa Minha Casa Minha Vida (MCMV) obtido pela candidata do governo Dilma Rousseff nos pleitos presidenciais. A votação eleitoral no Brasil é influenciada por uma série de características não observadas, tais como clientelismo, coronelismo, preferências individuais, voto de cabresto etc. Se tais características não forem levadas em conta na análise, o retorno eleitoral de programas sociais como MCMV e Bolsa-Família pode não ser adequadamente captado. Para contornar isso, foram estimadas regressões usando dados em painel com controle de efeitos fixos em nível microrregional. Os resultados revelam que há evidência de retorno eleitoral nulo do MCMV. Ao contrário, constatou-se ainda a existência de retorno eleitoral do Bolsa-Família em todas as regressões.
The aim of this study is to analyze the electoral return of the Minha Casa Minha Vida Program (MCMV) obtained by the incumbent candidate Dilma Rousseff in the presidential elections. Brazilian polls are affected by various non-observed characteristics, such as patronage, "coronelismo", individual preferences, "voto de cabresto" etc. If these characteristics are not taken into account in the analysis, the electoral return of social programs like MCMV and Bolsa-Familia (BF) cannot be properly captured. To solve this problem, a fixed effect model was estimated at the micro-regional level. The findings reveal that there is evidence of electoral return null of MCMV. Still, the electoral return of BF program was verified in all estimated regressions.
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Talukdar, Muhammad Bakhtear U. "CFO Turnover, Firm’s Debt-Equity Choice and Information Environment." FIU Digital Commons, 2016. http://digitalcommons.fiu.edu/etd/2618.
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The CEO and CFO are the two key executives of a firm. They work cohesively to ensure the growth of the firm. After the adoption of the Sarbanes Oxley Act (SOX) in 2002, the importance of CFOs has increased due to their personal legal obligation in certifying the accuracy of financial statements. Only a few papers such as Mian (2001), Fee and Hadlock (2004), and Geiger and North (2006) focus on CFOs in the pre-SOX era. However, a vacuum exists in research focusing exclusively on CFOs in the post-SOX era. The purpose of this dissertation is to delve into a comprehensive investigation of the CFOs. More specifically, I answer three questions: a) does the CEO change lead to the CFO change? b) does the CFO appointment type affect the firm’s debt-equity choice? and c) does the CFO appointment affect the firm’s information environment?
I use Shumway’s (2001) dynamic hazard model in answering question ‘a’. For question ‘b’, I use instrumental variable (IV) regression under various estimation techniques to control for endogeneity. For part ‘c’, I use the cross sectional difference-in-difference (DND) methodology by pairing treatment firms with control firms chosen by the propensity scores matching (PSM).
I find there is about a 70% probability of CFO replacement after the CEO replacement. Both of their replacements are affected by prior year’s poor performance. In addition, as a custodian of the firm’s financial reporting, the CFO is replaced proactively due to a probability of restatement of earnings. I find firms with internal CFO hires issue more equity in the year of appointment than firms with external hires. The promoted CFO significantly improves the firm’s overall governance which helps the firm obtain external financing from equity issue. However, I find that CFO turnover does not significantly affect the firm’s information environment. To ensure that my finding is not due to mixing up of samples of good and distressed firms together, I separated distressed firms and re-ran my models and my finding still holds.
This dissertation fills the gap in the literature with regards to CFOs and their post SOX relationship with the firm.
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Zharova, Alona. "Measures of University Research Output." Doctoral thesis, Humboldt-Universität zu Berlin, 2018. http://dx.doi.org/10.18452/18799.
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New Public Management unterstützt Universitäten und Forschungseinrichtungen dabei, in einem stark wettbewerbsorientierten Forschungsumfeld zu bestehen. Entscheidungen unter Unsicherheit, z.B. die Verteilung von Mitteln für den Forschungsbedarf und Forschungszwecke, erfordert von Politik und Hochschulmanagement, die Beziehungen zwischen den Dimensionen der Forschungsleistung und den resultierenden oder eingehenden Zuschüssen zu verstehen. Hierfür ist es wichtig, die Variablen der wissenschaftlichen Wissensproduktion auf der Ebene von Individuen, Forschungsgruppen und Universitäten zu untersuchen.
Das Kapitel 2 dieser Arbeit analysiert die Ebene der Individuen. Es verwendet die Beobachtungen der Forscherprofile von Handelsblatt (HB), Research Papers in Economics (RePEc, hier RP) und Google Scholar (GS) als meist verbreitete Ranking-Systeme in BWL und VWL im deutschsprachigen Raum.
Das Kapitel 3 liefert eine empirische Evidenz für die Ebene von Forschungsgruppen und verwendet die Daten eines Sonderforschungsbereichs (SFB) zu Finanzinputs und Forschungsoutput von 2005 bis 2016. Das Kapitel beginnt mit der Beschreibung passender Performanzindikatoren, gefolgt von einer innovativen visuellen Datenanalyse. Im Hauptteil des Kapitels untersucht die Arbeit mit Hilfe eines Zeit-Fixed-Effects-Panel- Modells und eines Fixed-Effects-Poisson-Modells den Zusammenhang zwischen finanziellen Inputs und Forschungsoutputs.
Das Kapitel 4 beschäftigt sich mit dem Niveau der Universitäten und untersucht die Interdependenzstruktur zwischen Drittmittelausgaben, Publikationen, Zitationen und akademischem Alter mit Hilfe eines PVARX-Modells, einer Impulsantwort und einer Zerlegung der Prognosefehlervarianz. Abschließend befasst sich das Kapitel mit den möglichen Implikationen für Politik und Entscheidungsfindung und schlägt Empfehlungen für das universitäre Forschungsmanagement vor.New Public Management helps universities and research institutions to perform in a highly competitive research environment. Decision making in the face of uncertainty, for example distribution of funds for research needs and purposes, urges research policy makers and university managers to understand the relationships between the dimensions of research performance and the resulting or incoming grants. Thus, it is important to accurately reflect the variables of scientific knowledge production on the level of individuals, research groups and universities. Chapter 2 of this thesis introduces an analysis on the level of individuals. The data are taken from the three widely-used ranking systems in the economic and business sciences among German-speaking countries: Handelsblatt (HB), Research Papers in Economics (RePEc, here RP) and Google Scholar (GS). It proposes a framework for collating ranking data for comparison purposes. Chapter 3 provides empirical evidence on the level of research groups using data from a Collaborative Research Center (CRC) on financial inputs and research output from 2005 to 2016. First, suitable performance indicators are discussed. Second, main properties of the data are described using visualization techniques. Finally, the time fixed effects panel data model and the fixed effects Poisson model are used to analyze an interdependency between financial inputs and research outputs. Chapter 4 examines the interdependence structure between third-party expenses (TPE), publications, citations and academic age using university data on individual performance in different scientific areas. A panel vector autoregressive model with exogenous variables (PVARX), impulse response functions and a forecast error variance decomposition help to capture the relationships in the system. To summarize, the chapter addresses the possible implications for policy and decision making and proposes recommendations for university research management.
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Ana, Knežević. "Primena panel modela u identifikovanju faktora uspešnosti poslovanja proizvodnih preduzeća." Phd thesis, Univerzitet u Novom Sadu, Fakultet tehničkih nauka u Novom Sadu, 2015. http://www.cris.uns.ac.rs/record.jsf?recordId=95568&source=NDLTD&language=en.
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Osnovni cilj istraživanja predstavlja identifikovanje faktorakoji utiču na uspešnost poslovanja proizvodnih preduzeća, i tokorišćenjem metodologije iz oblasti analize panel podataka.Kao mera uspešnosti poslovanja korišćena je profitabilnost.Istraživanjem je obuhvaćena analiza uticaja nekoliko internih ieksternih faktora. Utvrđen je značajan uticaj kako internih(veličina preduzeća, finansijska zaduženost, efikasnostkorišćenja imovine i stopa opipljivosti imovine) tako ieksternih (inflacija, BDP i kamatne stope) faktora nauspešnost poslovanja proizvodnih preduzeća.The main goal of this research is identifying factors that have an impact onbusiness success of the manufacturing companies, by using themethodology of panel models analysis. Profitability is used as a measure ofbusiness success. Research involves analysis of several internal andexternal factors.Significant influence of several internal (size, financial leverage, efficiency ofassets usage and tangibility of assets) and external factors (inflation, GDPand interest rates) on business success of manufacturing companies hasbeen identified.
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Abdel-Salam, Abdel-Salam Gomaa. "Profile Monitoring with Fixed and Random Effects using Nonparametric and Semiparametric Methods." Diss., Virginia Tech, 2009. http://hdl.handle.net/10919/29387.
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Profile monitoring is a relatively new approach in quality control best used where the process data follow a profile (or curve) at each time period. The essential idea for profile monitoring is to model the profile via some parametric, nonparametric, and semiparametric methods and then monitor the fitted profiles or the estimated random effects over time to determine if there have been changes in the profiles. The majority of previous studies in profile monitoring focused on the parametric modeling of either linear or nonlinear profiles, with both fixed and random effects, under the assumption of correct model specification.
Our work considers those cases where the parametric model for the family of profiles is unknown or at least uncertain. Consequently, we consider monitoring profiles via two techniques, a nonparametric technique and a semiparametric procedure that combines both parametric and nonparametric profile fits, a procedure we refer to as model robust profile monitoring (MRPM). Also, we incorporate a mixed model approach to both the parametric and nonparametric model fits. For the mixed effects models, the MMRPM method is an extension of the MRPM method which incorporates a mixed model approach to both parametric and nonparametric model fits to account for the correlation within profiles and to deal with the collection of profiles as a random sample from a common population.
For each case, we formulated two Hotelling's T 2 statistics, one based on the estimated random effects and one based on the fitted values, and obtained the corresponding control limits. In addition,we used two different formulas for the estimated variancecovariance matrix: one based on the pooled sample variance-covariance matrix estimator and a second one based on the estimated variance-covariance matrix based on successive differences.
A Monte Carlo study was performed to compare the integrated mean square errors (IMSE) and the probability of signal of the parametric, nonparametric, and semiparametric approaches. Both correlated and uncorrelated errors structure scenarios were evaluated for varying amounts of model misspecification, number of profiles, number of observations per profile, shift location, and in- and out-of-control situations. The semiparametric (MMRPM) method for uncorrelated and correlated scenarios was competitive and, often, clearly superior with the parametric and nonparametric over all levels of misspecification. For a correctly specified model, the IMSE and the simulated probability of signal for the parametric and theMMRPM methods were identical (or nearly so).
For the severe modelmisspecification case, the nonparametric andMMRPM methods were identical (or nearly so). For the mild model misspecification case, the MMRPM method was superior to the parametric and nonparametric methods. Therefore, this simulation supports the claim that the MMRPM method is robust to model misspecification.
In addition, the MMRPM method performed better for data sets with correlated error structure. Also, the performances of the nonparametric and MMRPM methods improved as the number of observations per profile increases since more observations over the same range of X generally enables more knots to be used by the penalized spline method, resulting in greater flexibility and improved fits in the nonparametric curves and consequently, the semiparametric curves.
The parametric, nonparametric and semiparametric approaches were utilized for fitting the relationship between torque produced by an engine and engine speed in the automotive industry. Then, we used a Hotelling's T 2 statistic based on the estimated random effects to conduct Phase I studies to determine the outlying profiles. The parametric, nonparametric and seminonparametric methods showed that the process was stable. Despite the fact that all three methods reach the same conclusion regarding the –in-control– status of each profile, the nonparametric and MMRPM results provide a better description of the actual behavior of each profile. Thus, the nonparametric and MMRPM methods give the user greater ability to properly interpret the true relationship between engine speed and torque for this type of engine and an increased likelihood of detecting unusual engines in future production. Finally, we conclude that the nonparametric and semiparametric approaches performed better than the parametric approach when the user's model is misspecified. The case study demonstrates that, the proposed nonparametric and semiparametric methods are shown to be more efficient, flexible and robust to model misspecification for Phase I profile monitoring in a practical application.
Thus, our methods are robust to the common problem of model misspecification. We also found that both the nonparametric and the semiparametric methods result in charts with good abilities to detect changes in Phase I data, and in charts with easily calculated control limits. The proposed methods provide greater flexibility and efficiency than current parametric methods used in profile monitoring for Phase I that rely on correct model specification, an unrealistic situation in many practical problems in industrial applications.Ph. D.
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Iwakura, Haruo. "Asymptotic Efficiency of Estimates for Panel Data Models with Fixed Effect." Kyoto University, 2014. http://hdl.handle.net/2433/188444.
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Du, Chenguang. "How Well Can Two-Wave Models Recover the Three-Wave Second Order Latent Model Parameters?" Diss., Virginia Tech, 2021. http://hdl.handle.net/10919/103856.
Full textAbstract:
Although previous studies on structural equation modeling (SEM) have indicated that the
second-order latent growth model (SOLGM) is a more appropriate approach to
longitudinal intervention effects, its application still requires researchers to collect at least
three-wave data (e.g. randomized pretest, posttest, and follow-up design). However, in
some circumstances, researchers can only collect two-wave data for resource limitations.
With only two-wave data, the SOLGM can not be identified and researchers often choose
alternative SEM models to fit two-wave data. Recent studies show that the two-wave
longitudinal common factor model (2W-LCFM) and latent change score model
(2W-LCSM) can perform well for comparing latent change between groups. However, there
still lacks empirical evidence about how accurately these two-wave models can estimate the
group effects of latent change obtained by three-wave SOLGM (3W-SOLGM). The main
purpose of this dissertation, therefore, is trying to examine to what extent the fixed effects
of the tree-wave SOLGM can be recovered from the parameter estimates of the two-wave
LCFM and LCSM given different simulation conditions.
Fundamentally, the supplementary study (study 2) using three-wave LCFM was
established to help justify the logistics of different model comparisons in our main study
(study 1). The data generating model in both studies is 3W-SOLGM and there are in total
5 simulation factors (sample size, group differences in intercept and slope, the covariance
between the slope and intercept, size of time-specific residual, change the pattern of
time-specific residual). Three main types of evaluation indices were used to assess the
quality of estimation (bias/relative bias, standard error, and power/type I error rate). The
results in the supplementary study show that the performance of 3W-LCFM and
3W-LCSM are equivalent, which further justifies the different models' comparison in the
main study. The point estimates for the fixed effect parameters obtained from the two-wave
models are unbiased or identical to the ones from the three-wave model. However, using
two-wave models could reduce the estimation precision and statistical power when the
time-specific residual variance is large and changing pattern is heteroscedastic
(non-constant). Finally, two real datasets were used to illustrate the simulation resultsDoctor of Philosophy
To collect and analyze the longitudinal data is a very important approach to understand the phenomenon of development in the real world. Ideally, researchers who are interested in using a longitudinal framework would prefer collecting data at more than two points in time because it can provide a deeper understanding of the developmental processes. However, in real scenarios, data may only be collected at two-time points. With only two-wave data, the second-order latent growth model (SOLGM) could not be used. The current dissertation compared the performance of two-wave models (longitudinal common factor model and latent change score model) with the three-wave SOLGM in order to better understand how the estimation quality of two-wave models could be comparable to the tree-wave model. The results show that on average, the estimation from two-wave models is identical to the ones from the three-wave model. So in real data analysis with only one sample, the point estimate by two-wave models should be very closed to that of the three-wave model. But this estimation may not be as accurate as it is obtained by the three-wave model when the latent variable has large variability in the first or last time point. This latent variable is more likely to exist as a statelike construct in the real world. Therefore, the current study could provide a reference framework for substantial researchers who could only have access to two-wave data but are still interested in estimating the growth effect that supposed to obtain by three-wave SOLGM.
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Gallina, Andrea. "Entrepreneurship and election timing." Master's thesis, Instituto Superior de Economia e Gestão, 2020. http://hdl.handle.net/10400.5/20906.
Full textAbstract:
Mestrado em FinançasO objetivo desta dissertação é examinar o impacto das eleições políticas na atividade empresarial. Para isso, coletamos dados de 16 países por um número variado de anos (dentro de uma faixa de 16 a 21 anos por país) para construir uma amostra de 3.056 observações. Os nossos dados vêm do Global Entrepreneurship Monitor Adult Population Survey e do Nordsieck, W. (1997) Parties and Elections in Europe, obtido em http://www.parties-and-elections.eu. Em seguida, estimamos um pooled Ordinary Least Squares (OLS) e um modelo de efeito fixo para ver como o momento das eleições afeta os níveis empresariais no país. Além disso, examinamos os efeitos de uma vitória inesperada. Os resultados obtidos sugerem que a Atividade Empreendedora Total aumenta durante um ano eleitoral e diminui no ano anterior, enquanto não há evidência estatística de qualquer efeito no ano seguinte.
Purpose of this dissertation is to examine the impact of political elections on entrepreneurial activity. In order to do so, we collect data from 17 countries for a varied number of years (within a range of 16 to 21 years per country) to build a sample of 3,056 observations. Our data comes from the Global Entrepreneurship Monitor Adult Population Survey and from Nordsieck, W. (1997) Parties and Elections in Europe retrieved from http://www.parties-and-elections.eu . We then estimate a pooled Ordinary Least Squares (OLS) and a fixed effect model to see how the elections timing affect entrepreneurial levels in the country. In addition, we examine the effects of an unexpected victory, Results obtained suggest that Total Entrepreneurial Activity increases during an election year and decreases the year before, while there is no statistical evidence of any effect in the year after.
info:eu-repo/semantics/publishedVersion
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Johnson, Jacqueline Laurel Catellier Diane J. Muller Keith E. "Fixed effects inference for clustered data in Gaussian linear models." Chapel Hill, N.C. : University of North Carolina at Chapel Hill, 2007. http://dc.lib.unc.edu/u?/etd,1366.
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Thesis (DrPH)--University of North Carolina at Chapel Hill, 2007.Title from electronic title page (viewed Apr. 25, 2008). "... in partial fulfillment of the requirements for the degree of Doctor of Public Health in the Department of Biostatistics, School of Public Health." Discipline: Biostatistics; Department/School: Public Health.
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Adjakossa, Eric Houngla. "Analyse longitudinale multivariée par modèles mixtes et application à l'épidémie de la malaria." Thesis, Paris 6, 2017. http://www.theses.fr/2017PA066014.
Full textAbstract:
Dans cette thèse, nous nous sommes focalisés sur le modèle statistique linéaire à effets mixtes. Nous nous sommes d'abord intéressés à l'estimation consistante des paramètres du modèle dans sa version multidimensionnelle, puis à de la sélection d'effets fixes en dimension un. En ce qui concerne l'estimation des paramètres du modèle linéaire à effets mixtes multidimensionnel, nous avons proposé des estimateurs du maximum de vraisemblance par utilisation de l'algorithme EM, mais avec des expressions plus générales que celles de la littérature classique, permettant d'analyser non seulement des données longitudinales multivariées mais aussi des données multidimensionnelles multi-niveaux. Ici, en s'appuyant sur ces EM-estimateurs, nous avons introduit un test de rapport de vraisemblance permettant de tester la significativité globale des corrélations entre les effets aléatoires de deux dimensions du modèle. Ce qui permettrait de construire un modèle multidimensionnel plus parcimonieux en terme de paramètres de variance des effets aléatoires, par une procédure de selection pas-à-pas ascendante. Cette démarche a été suscitée par le fait que la dimension du vecteur de tous les effets aléatoires du modèle peut très rapidement croitre avec le nombre de variables à analyser, entrainant facilement des problèmes numériques dans l'optimisation du critère choisi (ML ou REML). Nous avons ensuite proposé une procédure d'estimation consistante des paramètres du modèle qui passe par la résolution d'un problème de moindres carrés pénalisés pour fournir une expression explicite de la déviance à minimiser. La procédure de sélection d'effets fixes proposée ici est de type adaptive ridge itérative et permet d'approximer les performances de sélection d'une pénalité de type L0 de la vraisemblance des paramètres du modèle. Nos résultats ont été appuyés par des études de simulation à plusieurs niveaux, mais aussi par l'analyse de plusieurs jeux de données réellesThis thesis focuses on the statistical linear mixed-effects model, where we have been interested in its multivariate version's parameters estimation but also in the unidimensional selection of fixed effects. Concerning the parameters estimation of the multivariate linear mixed-effects model, we have first introduced more general expressions of the EM algorithm-based estimators which fit the multivariate longitudinal data analysis framework but also the framework of the multivariate multilevel data analysis. Since the dimensionality of the total vector of random effects in the multivariate model can grow with the number of the outcome variables leading often to computational problems in the likelihood optimization, we introduced a likelihood ratio test for testing the global effect of the correlations between the random effects of two dimensions of the model. This bivariate correlation test is intended to help in constructing a more parsimonious model regarding the variance components of the random effects, using a stepwise procedure. Secondly, we have introduced another estimation procedure that yields to consistent estimates for all the model parameters. This procedure is based on the Cholesky factorization of the random effects covariance matrix and the resolution of a preliminary penalized means square problem, and leads to an explicite expression of the profiled deviance of the model. For selecting fixed effects in the one dimensional mixed-effects model, we introduce an iterative adaptive ridge procedure for approximating sL0 penalty selection performances. All the results in this manuscript have been accompanied by extensive simulation studies along with real data analysis examples
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Li, Zhengrong. "Model-based Tests for Standards Evaluation and Biological Assessments." Diss., Virginia Tech, 2006. http://hdl.handle.net/10919/29108.
Full textAbstract:
Implementation of the Clean Water Act requires agencies to monitor aquatic sites on a regular basis and evaluate the quality of these sites. Sites are evaluated individually even though there may be numerous sites within a watershed. In some cases, sampling frequency is inadequate and the evaluation of site quality may have low reliability.
This dissertation evaluates testing procedures for determination of site quality based on modelbased procedures that allow for other sites to contribute information to the data from the test site. Test procedures are described for situations that involve multiple measurements from sites within a region and single measurements when stressor information is available or when covariates are used to account for individual site differences.
Tests based on analysis of variance methods are described for fixed effects and random effects models. The proposed model-based tests compare limits (tolerance limits or prediction limits) for the data with the known standard. When the sample size for the test site is small, using model-based tests improves the detection of impaired sites. The effects of sample size, heterogeneity of variance, and similarity between sites are discussed. Reference-based standards and corresponding evaluation of site quality are also considered. Regression-based tests provide methods for incorporating information from other sites when there is information on stressors or covariates.
Extension of some of the methods to multivariate biological observations and stressors is also discussed. Redundancy analysis is used as a graphical method for describing the relationship between biological metrics and stressors. A clustering method for finding stressor-response relationships is presented and illustrated using data from the Mid-Atlantic Highlands. Multivariate elliptical and univariate regions for assessment of site quality are discussed.Ph. D.
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Loy, Jens-Peter, and Christoph Weiss. "Synchronisation in multi-product firms. Evidence from german grocery prices." Inst. für Volkswirtschaftstheorie und -politik, WU Vienna University of Economics and Business, 2003. http://epub.wu.ac.at/300/1/document.pdf.
Full textAbstract:
Using a unique panel data set for German grocery prices we find significant price synchronization within food retail chains as well as within individual food stores (between products). Price synchronization between chains appears to be less pronounced. Common shocks can only explain some synchronization, indicating that strategic motives as well as menu costs are of significant importance. (author's abstract)Series: Working Papers Series "Growth and Employment in Europe: Sustainability and Competitiveness"
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Du, Ye Ting. "Simultaneous fixed and random effects selection in finite mixtures of linear mixed-effects models." Thesis, McGill University, 2012. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=110592.
Full textAbstract:
Linear mixed-effects (LME) models are frequently used for modeling longitudinal data. One complicating factor in the analysis of such data is that samples are sometimes obtained from a population with significant underlying heterogeneity, which would be hard to capture by a single LME model. Such problems may be addressed by a finite mixture of linear mixed-effects (FMLME) models, which segments the population into subpopulations and models each subpopulation by a distinct LME model. Often in the initial stage of a study, a large number of predictors are introduced. However, their associations to the response variable vary from one component to another of the FMLME model. To enhance predictability and to obtain a parsimonious model, it is of great practical interest to identify the important effects, both fixed and random, in the model. Traditional variable selection techniques such as stepwise deletion and subset selection are computationally expensive even with modest numbers of covariates and components in the mixture model. In this thesis, we introduce a penalized likelihood approach and propose a nested EM algorithm for efficient numerical computations. The estimators are shown to possess consistency and sparsity properties and asymptotic normality. We illustrate the performance of the proposed method through simulations and a real data example.Les modèles linéaires mixtes (LME) sont fréquemment employés pour la modélisation des données longitudinales. Un facteur qui complique l'analyse de ce genre de données est que les échantillons sont parfois obtenus à partir d'une population d'importante hétérogénéité sous-jacente, qui serait difficile à capter par un seul LME. De tels problèmes peuvent être surmontés par un mélange fini de modèles linéaires mixtes (FMLME), qui segmente la population en sous-populations et modélise chacune de ces dernières par un LME distinct. Souvent, un grand nombre de variables explicatives sont introduites dans la phase initiale d'une étude. Cependant, leurs associations à la variable réponse varient d'un composant à l'autre du modèle FMLME. Afin d'améliorer la prévisibilité et de recueillir un modèle parcimonieux, il est d'un grand intérêt pratique d'identifier les effets importants, tant fixes qu'aléatoires, dans le modèle. Les techniques conventionnelles de sélection de variables telles que la suppression progressive et la sélection de sous-ensembles sont informatiquement chères, même lorsque le nombre de composants et de covariables est relativement modeste. La présente thèse introduit une approche basée sur la vraisemblance pénalisée et propose un algorithme EM imbriqué qui est computationnellement efficace. On démontre aussi que les estimateurs possèdent des propriétés telles que la cohérence, la parcimonie et la normalité asymptotique. On illustre la performance de la méthode proposée au moyen de simulations et d'une application sur un vrai jeu de données.
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Gumprecht, Daniela. "R&D Spillovers: A Non-Spatial and a Spatial Examination." Austrian Statistical Society, c/o Bundesanstalt Statistik Austria, 2007. http://epub.wu.ac.at/5388/1/316%2D1053%2D1%2DSM.pdf.
Full textAbstract:
In recent years there were many debates and different opinions
whether R&D spillover effects exist or not. In 1995 Coe and Helpman published
a study about this phenomenon, based on a panel dataset, that supports
the position that such R&D spillover effects are existent. However, this
survey was criticized and many different suggestions for improvement came
from the scientific community. Some of them were selected and analysed and
finally led to a new model. And even though this new model is well compatible
with the data, it leads to different conclusions, namely that there does
not exist an R&D spillover effect. These different results were the motivation
to run a spatial analysis, which can be done by considering the countries as
regions and using an adequate spatial link matrix. The used methods from
the field of spatial econometrics are described briefly and quite general, and
finally the results from the spatial models (the ones which correspond to the
non-spatial ones) are compared with the results from the non-spatial analysis.
The preferred model supports the position that R&D spillover effects exist.
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Cook, Amy W. "Predictive models to support quoting of fixed fee consulting projects." Thesis, Queensland University of Technology, 2017. https://eprints.qut.edu.au/104557/1/Amy_Cook_Thesis.pdf.
Full textAbstract:
This thesis tackled a problem faced by consulting companies in the construction industry, where a significant proportion of projects result in losses. This occurs despite managers’ best efforts to price and execute projects profitably. Several machine learning and statistical techniques were applied to a case study company’s historic timesheet, client, and invoicing data in order to predict loss-making projects. The algorithms were tested in a simulated business decision-making scenario and the best model improved profits by 9%. The work from this research makes a step towards helping businesses reduce risk by integrating their data into financial decisions.
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Pelagia, Ioanna. "Variable selection of fixed effects and frailties for Cox Proportional Hazard frailty models and competing risks frailty models." Thesis, University of Manchester, 2016. https://www.research.manchester.ac.uk/portal/en/theses/variable-selection-of-fixed-effects-and-frailties-for-cox-proportional-hazard-frailty-models-and-competing-risks-frailty-models(c75c6314-f43e-4d69-a2de-942bece6a404).html.
Full textAbstract:
This thesis focuses on two fundamental topics, specifically in medical statistics: the modelling of correlated survival datasets and the variable selection of the significant covariates and random effects. In particular, two types of survival data are considered: the classical survival datasets, where subjects are likely to experience only one type of event and the competing risks datasets, where subjects are likely to experience one of several types of event. In Chapter 2, among other topics, we highlight the importance of adding frailty terms on the proposed models in order to account for the association between the survival time and characteristics of subjects/groups. The main novelty of this thesis is to simultaneously select fixed effects and frailty terms through the proposed statistical models for each survival dataset. Chapter 3 covers the analysis of the classical survival dataset through the proposed Cox Proportional Hazard (PH) model. Utilizing a Cox PH frailty model, may increase the dimension of variable components and estimation of the unknown coefficients becomes very challenging. The method proposed for the analysis of classical survival datasets involves simultaneous variable selection on both fixed effects and frailty terms through penalty functions. The benefit of penalty functions is that they identify the non-significant parameters and set them to have a zero effect in the model. Hence, the idea is to 'doubly-penalize' the partial likelihood of the Cox PH frailty model; one penalty for each term. Estimation and selection implemented through Newton-Raphson algorithms, whereas closed iterative forms for the estimation and selection of fixed effects and prediction of frailty terms were obtained. For the selection of frailty terms, penalties imposed on their variances since frailties are random effects. Based on the same idea, we further extend the simultaneous variable selection in the competing risks datasets in Chapter 4, using extended cause-specific frailty models. Two different scenarios are considered for frailty terms; in the first case we consider that frailty terms vary among different types of events (similar to the fixed effects) whereas in the second case we consider shared frailties over all the types of events. Moreover, our 'individual penalization' approach allows for one covariate to be significant for some types of events, in contrast to the frequently used 'group-penalization' where a covariate is entirely removed when it is not significant over all the events. For both proposed methods, simulation studies were conduced and showed that the proposed procedure followed for each analysis works well in simultaneously selecting and estimating significant fixed effects and frailty terms. The proposed methods are also applied to real datasets analysis; Kidney catheter infections, Diabetes Type 2 and Breast Cancer datasets. Association of the survival times and unmeasured characteristics of the subjects was studied as well as a variable selection for fixed effects and frailties implemented successfully.
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Mansour, Asmaa. "Modeling outcome estimates in meta-analysis using fixed and mixed effects linear models." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape11/PQDD_0001/MQ44216.pdf.
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Mansour, Asmaâ. "Modeling outcome estimates in meta-analysis using fixed and mixed effects linear models." Thesis, McGill University, 1998. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=20585.
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The main objective of this thesis is to present a quantitative method for modeling data collected from different studies on a same research topic. This quantitative method is called meta-analysis.The first step of a meta-analysis is the literature search, conducted using computerized and manual search strategies to identify relevant studies. The second step is the data abstraction from different relevant papers. In general, at least two independent raters systematically abstract the information, and interrater reliability check is performed.
The next step is the quantitative analysis of the abstracted data. For this purpose, it is possible to use either fixed or mixed effects linear model. Under the fixed effects model, only the variability due to sampling error is considered. In contrast, under the mixed effects model, an additional random effects variance is being considered. Both, the method of moments and the method of maximum likelihood can be used to estimate the parameters of the model.
Finally, the use of the above mentioned models and methods of estimation is illustrated with a data set on the prognosis of depression in the elderly, made available by Dr. Martin Cole from the Department of Psychiatry at St. Mary's Hospital Center in Montreal.
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Dudokh, Dana. "What factors affect the destination choice of Jordanian tourists?A panel data analysis." Thesis, Högskolan Dalarna, Företagsekonomi, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:du-3725.
Full textAbstract:
This paper investigates what factors affect the destination choice for Jordanian to 8 countries (Oman, Saudi Arabia, Syria, Tunisia, Yemen, Egypt, Lebanon and Bahrain) using panel data analysis. Number of outbound tourists is represented as dependent variable, which is regressed over five explanatory variables using fixed effect model. The finding of this paper is that tourists from Jordan have weak demand for outbound tourism; Jordanian decision of traveling abroad is determined by the cost of traveling to different places and choosing the cheapest alternative.
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Akolly, Kokou S. "Looking in the Crystal Ball: Determinants of Excess Return." Digital Archive @ GSU, 2010. http://digitalarchive.gsu.edu/math_theses/87.
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This paper investigates the determinants of excess returns using dividend yields as a proxy in a cross-sectional setting. First, we find that types of industry and the current business cycle are determining factors of returns. Second, our results suggest that dividend yield serves a signaling mechanism indicating “healthiness” of a firm among prospective investors. Third we see that there is a positive relationship between dividend yield and risk, especially in the utility and financial sectors. And finally, using actual excess returns, instead of dividend yield in our model shows that all predictors of dividend yield were also significant predictors of excess returns. This connection between dividend yield and excess returns support our use of dividend yield as a proxy for excess returns.
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Koort, Anna, and Karin Zetterberg. "Reagerar sjukskrivna för psykiska besvär annorlunda på en ersättningsförändring i sjukförsäkringen jämfört med övriga sjukskrivna? : En empirisk undersökning för perioden 1996-1999." Thesis, Uppsala University, Department of Economics, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-6355.
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Syftet med denna uppsats är att undersöka om de som är sjukskrivna med diagnosen psykisk sjukdom reagerar annorlunda vid ersättningsförändringen i sjukförsäkringen år 1998 jämfört med övriga sjukskrivna. I detta syfte har vi tillämpat två Fixed effects modeller på paneldata över en fyraårsperiod, 1996 till 1999, som innefattar Sveriges län. Som approximation på andelen med psykisk sjukdom bland de sjukskrivna har vi använt Apotekets statistik över konsumtionen av antidepressiva medel och sömn- och lugnande medel. Under förutsättning att läkemedelskonsumtion är en god approximation för andelen med psykisk sjukdom i länen. Får vi ett statistisk signifikant resultat som tyder på att andelen med psykisk sjukdom bland de sjukskrivna reagerar mindre positivt på ersättningsförändringen år 1998 jämfört med övriga sjukskrivna.
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Derin, Pinar. "Endogenous Growth Testing In The European Union And Developing Countries: Taxation, Public Expenditure And Growth." Master's thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/1112127/index.pdf.
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In endogenous growth models, in contrast to the neoclassical growth models,
government expenditure and taxation have an effect on the long run growth rate. In
this thesis I examine whether the empirical evidence support the predictions of
endogenous growth models or the neoclassical growth models in relation to fiscal
policy. For this purpose I use panel data for fifteen European Union (EU) member and
thirty-three developing countries between the years 1970 and 1999. I specifically test
the following two propositions. The first proposition states that distortionary taxation
decreases growth while non-distortionary taxation does not. The second, states that
productive government expenditure increases growth while non-productive
expenditure does not. The empirical results are quite different between European Union countries and developing countries. The results do not support endogenous
growth especially for developing countries.
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Badinger, Harald, and Peter Egger. "Fixed Effects and Random Effects Estimation of Higher-Order Spatial Autoregressive Models with Spatial Autoregressive and Heteroskedastic Disturbances." WU Vienna University of Economics and Business, 2014. http://epub.wu.ac.at/4126/1/wp173.pdf.
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This paper develops a unified framework for fixed and random effects estimation of higher-order spatial autoregressive panel data models with spatial autoregressive
disturbances and heteroskedasticity of unknown form in the idiosyncratic error component. We derive the moment conditions and optimal weighting matrix without distributional assumptions for a generalized moments (GM) estimation procedure of the spatial autoregressive parameters of the disturbance process and define both a random effects and a fixed effects spatial generalized two-stage least squares estimator for the regression parameters of the model. We prove consistency of the proposed estimators and derive their joint asymptotic distribution, which is robust to heteroskedasticity of unknown form in the idiosyncratic error component. Finally, we derive a robust Hausman-test of the spatial random against the spatial fixed effects model. (authors' abstract)Series: Department of Economics Working Paper Series
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Lawal, Fadekemi. "Impact of Corruption on Economic Growth : A panel data study of selected African countries." Thesis, Högskolan Dalarna, Nationalekonomi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:du-30218.
Full textAbstract:
African countries have over the last few decades, experienced a thorny path towards sustained economic growth. Quite a number of researchers have opined that a major factor responsible for their stunted growth path is the prevalence of corruption in the governments of many African countries. However, a group of scholars, called revisionists, have suggested that corruption actually acts as grease in the wheel that ensures the smooth running of an economy, by providing a mechanism to evade inefficient bureaucratic procedures and allow more equitable representation of minority members of the society. With the increasing exposure of African economies to the international community, there is a need to examine the obtainable evidence in relation to corruption and economic growth in African countries. This thesis, therefore, aims to establish the nature of the relationship between corruption and economic growth in the selected African countries. The growth rate of gross domestic product per capita is used to represent the variable, economic growth. The study employs the use of panel data fixed effects and random effect estimation techniques, across 18 countries, over the period of 1997 – 2016. The results show that corruption has a positive relationship with economic growth in the selected African countries. This is in line with the grease in the wheel argument for corruption proposed by revisionists. The results also indicate that corruption has a moderately significant impact on economic growth at 10% level of significance. The literature review suggests that corruption affects economic growth directly and indirectly through mechanisms such as investment (private and public), human capital, openness, and institutional mechanisms, among others.
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Sax, Kaijser Per. "Tobin’s Q theory and regional housing investment : Empirical analysis on Swedish data." Thesis, Uppsala universitet, Nationalekonomiska institutionen, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-226661.
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This thesis investigates the relationship between Tobin’s Q and regional housing investment in Sweden for the time period of 1998-2012. The relationship is tested through estimation of two models for time-series analysis, a vector error correction model (VECM) and an autoregressive distributed lag (ARDL) model. Depending on which model that is used, I find some evidence of positive correlation between Tobin’s Q and regional housing investment in the long run while the short run dynamics of investment does not seem to be explained by Tobin’s Q. By transforming the regional data into a panel data set and running a fixed effects model, I examine the gain in explanatory power of Tobin’s Q from using disaggregated data rather than aggregated. My findings suggest that using disaggregated data improves the explanatory power of Tobin’s Q on investment. However, the Granger Causality test indicates two-way causality between Tobin’s Q and investment, causing endogeneity problem in the estimated equations.
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Aaron, Lisa Therese. "A comparative simulation of Type I error and Power of Four tests of homogeneity of effects for random- and fixed-effects models of meta-analysis." [Tampa, Fla.] : University of South Florida, 2003. http://purl.fcla.edu/fcla/etd/SFE0000222.
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Stammann, 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.
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Galal, Ushma. "The statistical theory underlying human genetic linkage analysis based on quantitative data from extended families." Thesis, University of the Western Cape, 2010. http://etd.uwc.ac.za/index.php?module=etd&action=viewtitle&id=gen8Srv25Nme4_2684_1361989724.
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Traditionally in human genetic linkage analysis, extended families were only used in the analysis of dichotomous traits, such as Disease/No Disease. For quantitative traits, analyses initially focused on data from family trios (for example, mother, father, and child) or sib-pairs. Recently however, there have been two very important developments in genetics: It became clear that if the disease status of several generations of a family is known and their genetic information is obtained, researchers can pinpoint which pieces of genetic material are linked to the disease or trait. It also became evident that if a trait is quantitative (numerical), as blood pressure or viral loads are, rather than dichotomous, one has much more power for the same sample size. This led to the
development of statistical mixed models which could incorporate all the features of the data, including the degree of relationship between each pair of family members. This is necessary because a parent-child pair definitely shares half their genetic material, whereas a pair of cousins share, on average, only an eighth. The statistical methods involved here have however been developed by geneticists, for their specific studies, so there does not seem to be a unified and general description of the theory underlying the methods. The aim of this dissertation is to explain in a unified and statistically comprehensive manner, the theory involved in the analysis of quantitative trait genetic data from extended families. The focus is on linkage analysis: what it is and what it aims to do.
There is a step-by-step build up to it, starting with an introduction to genetic epidemiology. This includes an explanation of the relevant genetic terminology. There is also an application section where an appropriate human genetic family dataset is analysed, illustrating the methods explained in the theory sections.
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Kersuzan, Claire. "Le devenir des orphelins au Burundi : analyse des conséquences de l’expérience précoce du décès parental dans un contexte de crise socio-politique." Thesis, Bordeaux 4, 2012. http://www.theses.fr/2012BOR40057/document.
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Ce travail se propose d’examiner les conséquences du décès parental précoce sur la trajectoire biographique des enfants, dans un régime de mortalité où la principale perturbation n’est pas le VIH/SIDA, mais une grave crise socio-politique. Le Burundi est l’un des épicentres du conflit traversé dans les années 90 par la région des Grands Lacs. A l’aide des données de l’Enquête Socio-Démographique et de Santé de la Reproduction (ESDSR) menée au Burundi en 2002, nous analysons l’impact du décès parental précoce sur un grand nombre de dimensions du parcours de vie des enfants burundais: mortalité, violence et exploitation sexuelle, séparation des membres de la fratrie, scolarité, entrée précoce dans le travail, ressources, conditions de l’héritage, entrée dans la vie reproductive et familiale. Ces analyses sont menées selon l’âge de l’enfant au moment du décès d’au moins un de ses parents, tout en cherchant à évaluer l’effet de la cause de décès des parents (crise/autre cause) sur les résultats obtenus. On montre que la perturbation du parcours de vie des enfants ayant précocement vécu le décès de leur père est mineure. A l’inverse l’expérience précoce de la mère ou du dernier parent survivant affecte la plupart des dimensions de la trajectoire biographique des enfants. La crise burundaise amplifie et, dans certains cas, transforme voire renverse la relation entre l’expérience précoce du décès d’au moins un parent et la trajectoire des enfants. L’orphelin à cause des massacres de masse de 1993 est un orphelin « politique » dont la protection et le soutien par les instances politiques, militaires, administratives et humanitaires est devenu un enjeu de la crise elle-mêmeThe aim of this paper is to analyze lifetime effects of parental death during childhood, in a country context where HIV/AIDS isn’t the main cause of death among young adults but deaths caused by a major socio-political crisis. During the 90’s, Burundi hosted the cradle of the regional conflict in the Great Lakes. A 2002 demographic, social and reproductive health survey in Burundi (ESDSR) will provide us the information required to analyze impact of early parental death, on a complex panel of life perspectives for children: mortality, violence and sexual abuse, separation of siblings, schooling, working at early age, resources, heritage, early marriage and age at first birth. These analyses are led by child age at early parental death, along with an attempt to estimate the effect from the cause of this death (crisis or other) on results. The strength of leading conclusions is consolidated by the mean of exchanging results, these results being derived from several analysis methods: bivariate and multivariate logistic models adapted or not to clustered data (standard, multilevel, marginal and fixed-effects logistic regressions).We bring lights on the minor effect of early father loss on child life trajectory. On the contrary, early mother or last living parent death experience affects almost every child life trajectory. Burundi crisis emphases but in some cases, reverses those effects from negative to positive. 1993 mass slaughters orphans are “political” orphans. Their political, military, administrative and humanitarian protections became part of the main goals, in the crisis itself
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Walter, Benjamin. "Two essays on the market for Bitcoin mining and one essay on the fixed effects logit model with panel data." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLG002/document.
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Ma thèse se compose de deux parties indépendantes. La première traite decrypto-économie et la seconde d’économétrie théorique. Dans le premier chapitre, je présente un modèle qui prédit la puissance de calcul totale déployée par les mineurs en utilisant le taux de change bitcoin / dollar. Le deuxième chapitre s’appuie sur une version simplifiée du précédent modèle pour faire le constat de l’inefficacité du protocole Bitcoin actuel et proposer un moyen simple de réduire la consommation d’électricité engendrée par cette cryptomonnaie. Le troisième chapitre explique comment identifier et estimer les bornes exactes de la région d’identification de l’effet marginal moyen dans un modèle logit avec effets fixes sur données de panelMy dissertation concatenates two independent parts. The first one dealswith crypto-economics whereas the second one is about theoretical econometrics. In the first chapter, I present a model which predicts bitcoin miners’ total computing power using the bitcoin / dollar exchange rate. The second chapter builds on a simplified version of the preceeding model to show to which extent the current Bitcoin protocol is inefficient and suggest a simple solution to lower the cryptocurrency’s electricity consumption. The third chapter explains how to identify and estimate the sharp bounds of the average marginal effect’s identification region in a fixed effects logit model with panel data
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Schaper, Andrew. "Informative Prior Distributions in Multilevel/Hierarchical Linear Growth Models: Demonstrating the Use of Bayesian Updating for Fixed Effects." Thesis, University of Oregon, 2014. http://hdl.handle.net/1794/18366.
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This study demonstrates a fully Bayesian approach to multilevel/hierarchical linear growth modeling using freely available software. Further, the study incorporates informative prior distributions for fixed effect estimates using an objective approach. The objective approach uses previous sample results to form prior distributions included in subsequent samples analyses, a process referred to as Bayesian updating. Further, a method for model checking is outlined based on fit indices including information criteria (i.e., Akaike information criterion, Bayesian information criterion, and deviance information criterion) and approximate Bayes factor calculations. For this demonstration, five distinct samples of schools in the process of implementing School-Wide Positive Behavior Interventions and Supports (SWPBIS) collected from 2008 to 2013 were used with the unit of analysis being the school. First, the within-year SWPBIS fidelity growth was modeled as a function of time measured in months from initial measurement occasion. Uninformative priors were used to estimate growth parameters for the 2008-09 sample, and both uninformative and informative priors based on previous years' samples were used to model data from the 2009-10, 2010-11, 2011-12, 2012-13 samples. Bayesian estimates were also compared to maximum likelihood (ML) estimates, and reliability information is provided. Second, an additional three examples demonstrated how to include predictors into the growth model with demonstrations for: (a) the inclusion of one school-level predictor (years implementing) of SWPBIS fidelity growth, (b) several school-level predictors (relative socio-economic status, size, and geographic location), and (c) school and district predictors (sustainability factors hypothesized to be related to implementation processes) in a three-level growth model. Interestingly, Bayesian models estimated with informative prior distributions in all cases resulted in more optimal fit indices than models estimated with uninformative prior distributions.
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Kang, Lei. "Reduced-Dimension Hierarchical Statistical Models for Spatial and Spatio-Temporal Data." The Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=osu1259168805.
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Nilsson, Maria. "Differences and similarities in work absence behavior : - empirical evidence from micro data." Doctoral thesis, Växjö universitet, Ekonomihögskolan, EHV, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:vxu:diva-626.
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This thesis consists of three self-contained essays about absenteeism. Essay I analyzes if the design of the insurance system affects work absence, i.e. the classic insurance problem of moral hazard. Several reforms of the sickness insurance system were implemented during the period 1991-1996. Using Negative binomial models with fixed effects, the analysis show that both workers and employers changed their behavior due to the reforms. We also find that the extent of moral hazard varies depending on work contract structures. The reforms reducing the compensation levels decreased workers’ absence, both the number of absent days and the number of absence spells. The reform in 1992, introducing sick pay paid by the employers, also decreased absence levels, which probably can be explained by changes in personnel policy such as increased use of monitoring and screening of workers. Essay II examines the background to gender differences in work absence. Women are found, as in many earlier studies, to have higher absence levels than men. Our analysis, using finite mixture models, reveals that there are a group of women, comprised of about 41% of the women in our sample, that have a high average demand of absence. Among men, the high demand group is smaller consisting of about 36% of the male sample. The absence behavior differs as much between groups within gender as it does between men and women. The access to panel data covering the period 1971-1991 enables an analysis of the increased gender gap over time. Our analysis shows that the increased gender gap can be attributed to changes in behavior rather than in observable characteristics. Essay III analyzes the difference in work absence between natives and immigrants. Immigrants are found to have higher absence than natives when measured as the number of absent days. For the number of absence spells, the pattern for immigrants and natives is about the same. The analysis, using panel data and count data models, show that natives and immigrants have different characteristics concerning family situation, work conditions and health. We also find that natives and immigrants respond differently to these characteristics. We find, for example, that the absence of natives and immigrants are differently related to both economic incentives and work environment. Finally, our analysis shows that differences in work conditions and work environment only can explain a minor part of the ethnic differences in absence during the 1980’s.
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Thomson, Dana. "Changing Circumstances, Changing Outcomes?: Longitudinal Relations Between Family Income, Cumulative Risk Exposure, And Children’s Educational Success." Thesis, Boston College, 2017. http://hdl.handle.net/2345/bc-ir:107592.
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Thesis advisor: Eric DearingEmerging research in developmental psychology and neuroscience suggests that childhood poverty is associated with high levels of exposure to multiple contextual risks, which cumulatively lead to persistent elevated stress levels that have a direct, as well an indirect (e.g., through parental processes), impact on child cognitive, academic, and socioemotional functioning (Evans & Kim, 2013). Such research has begun to change the way that scholars and practitioners envision the context of poverty, the persistence of the income-achievement gap, and the types of interventions that may be most effective in addressing disparities in children’s long-term educational success. However, research on the relations between poverty-associated stress and child outcomes is still in its infancy and many questions remain. In particular, it is unclear whether changing family economic circumstances matter, a question of concern for developmental science and public policy. Moreover, there is little work on moderators of relations between income, stress, and child outcomes, which could help identify factors that buffer children from the harm of stressful home environments. With longitudinal data from the Panel Study of Income Dynamics’ Child Development Supplement, the present study used fixed effects models to examine within-child associations between changes in family income, cumulative risk exposure (as measured by an index that includes a range of poverty-related stressors, such as economic strain, neighborhood crime, and physical and psychological home environments), and children’s cognitive, academic and socioemotional functioning. In addition, moderators of these associations were investigated in order to identify potential protective mechanisms and crucial levers for interventions and policy development. On the whole, findings were consistent with the cumulative stress model. On average, the estimated direct effects of changes in family income (i.e., prior to examining mediation or moderators) were not significant for changes in child outcomes. Yet, changes in income were, for the sample as a whole, indirectly related via changes in cumulative risk exposure: increases in income predicted decreases in cumulative risk exposure which, in turn, predicted improvements in achievement and declines in externalizing behavior. Additionally, these relations were moderated by child age, initial level of family income, and initial level of cumulative risk
Thesis (PhD) — Boston College, 2017
Submitted to: Boston College. Lynch School of Education
Discipline: Counseling, Developmental and Educational Psychology
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Ottosson, Martin. "Jobbskatteavdraget och dess effekter på sysselsättningen - En difference-in-differences analys av reformens tre första år." Thesis, Uppsala universitet, Nationalekonomiska institutionen, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-144623.
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I denna studie undersöks hur införandet av jobbskatteavdraget 2007 och de två utbyggnaderna 2008-2009 påverkade arbetsmarknaden i form av sysselsättning, arbetslöshet, långtidsarbetslöshet och sysselsättning i åldersgruppen 55-64 år. Med utgångspunkt från en tillämpning av konsumtionsteorin, med arbetsutbudet i fokus, så görs en difference-in-differences analys av reformens tre första år i jämförelse med tre år innan dess införande. Resultaten visar att införandet av jobbskatteavdraget har haft en positiv effekt på arbetsmarknaden i form av en större andel avbefolkningen i arbete, medan ytterliggare steg av jobbskatteavdraget ger estimat som tyder på att effekten blir en minskad aktivitet på arbetsmarknaden.
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Fischer, Manfred M., Nico Pintar, and Benedikt Sargant. "Austrian Outbound Foreign Direct Investment in Europe: A spatial econometric study." The Romanian Regional Science Association, 2016. http://epub.wu.ac.at/5118/1/V1011.MMFischer.pdf.
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This paper focuses on Austrian outbound foreign direct investment (FDI, measured by sales of Austrian affiliates abroad) in Europe over the period 2009-2013, using a spatial Durbin panel data model specification with fixed effects, and a spatial weight matrix based on the first-order contiguity relationship of the countries and normalised by its largest eigenvalue. Third-country effects essentially enter the empirical analysis in two major ways: first, by the endogenous spatial lag on FDI (measured by FDI into markets nearby the host country), and, second, by including an exogenous market potential variable that measures the size of markets nearby the FDI host country in terms of gross domestic product. The question whether the empirical result is compatible with horizontal, vertical, export-platform or complex vertical FDI then depends on the sign and significance levels of both the coefficient of the spatial lag on FDI and the direct impact estimate of the market potential variable.
The paper yields robust results that provide significant empirical evidence for horizontal FDI as the main driver of Austrian outbound FDI in Europe. This result is strengthened by the indirect impact estimate of the mark
et potential variable indicating that spatial spillovers do not matter. (authors' abstract)