Statistical analysis of survey-based event history data with application to modeling of unemployment duration

Longitudinal surveys are increasingly used to collect event history data on person-specific processes such as transitions between labour market states. Surveybased event history data pose a number of challenges for statistical analysis. These challenges include survey errors due to sampling, non-response, attrition and measurement. This study deals with non-response, attrition and measurement errors in event history data and the bias caused by them in event history analysis. The study also discusses some choices faced by a researcher using longitudinal survey data for event history analysis and demonstrates their effects. These choices include, whether a design-based or a model-based approach is taken, which subset of data to use and, if a design-based approach is taken, which weights to use. The study takes advantage of the possibility to use combined longitudinal survey register data. The Finnish subset of European Community Household Panel (FI ECHP) survey for waves 1–5 were linked at person-level with longitudinal register data. Unemployment spells were used as study variables of interest. Lastly, a simulation study was conducted in order to assess the statistical properties of the Inverse Probability of Censoring Weighting (IPCW) method in a survey data context. The study shows how combined longitudinal survey register data can be used to analyse and compare the non-response and attrition processes, test the missingness mechanism type and estimate the size of bias due to non-response and attrition. In our empirical analysis, initial non-response turned out to be a more important source of bias than attrition. Reported unemployment spells were subject to seam effects, omissions, and, to a lesser extent, overreporting. The use of proxy interviews tended to cause spell omissions. An often-ignored phenomenon classification error in reported spell outcomes, was also found in the data. Neither the Missing At Random (MAR) assumption about non-response and attrition mechanisms, nor the classical assumptions about measurement errors, turned out to be valid. Both measurement errors in spell durations and spell outcomes were found to cause bias in estimates from event history models. Low measurement accuracy affected the estimates of baseline hazard most. The design-based estimates based on data from respondents to all waves of interest and weighted by the last wave weights displayed the largest bias. Using all the available data, including the spells by attriters until the time of attrition, helped to reduce attrition bias. Lastly, the simulation study showed that the IPCW correction to design weights reduces bias due to dependent censoring in design-based Kaplan-Meier and Cox proportional hazard model estimators. The study discusses implications of the results for survey organisations collecting event history data, researchers using surveys for event history analysis, and researchers who develop methods to correct for non-sampling biases in event history data.

Fiber flows in global paper and pulp industry. A panel data approach.

The purpose of this thesis is to study factors that explain the bilateral fiber trade flows. This is done by analyzing bilateral trade flows during 1990-2006. It will be studied also, whether there are differences between fiber types. This thesis uses a gravity model approach to study the trade flows. Gravity model is mostly used to study the aggregate data between trading countries. In this thesis the gravity model is applied to single fibers. This model is then applied to panel data set. Results from the regression show clearly that there are benefits in studying different fibers in separate. The effects differ considerably from each other. Furthermore, this thesis speaks for the existence of Linder’s effect in certain fiber types.

Contrasting tree-ring data with fire record in a pine-dominated landscape in the Komi Republic (Eastern European Russia) : recovering a common climate signal

Abstract

A comparison of one- and two-compartment neighbourhoods in heuristic search with spatial forest management goals

Abstract

Effects of Foreign Direct Investment inflows on growth in Central and Eastern European transition countries

The aim of this master’s thesis is to analyze the effects of Foreign Direct Investments on growth in selected Central and Eastern European transition countries. The theoretical part of this thesis, introduces growth theories and how FDI is covered in those theories. In addition, the results from previous studies, which have studied FDI’s effect on growth, are presented in this master’s thesis. This work introduces also the economical progress during the transition period in selected countries. In the empirical part’s regression model, it will be searched for the direct effect of FDI on growth with panel data collected from nine transition countries.

Effects of bank supervision and regulation on bank risk

In the last few decades, banking has strongly internationalized and become more complex. Hence, bank supervision and regulation has taken global perspective, too. The most important international regulation are the Basel frameworks by the Basel committee on banking supervision. This study examines the effects of bank supervision and regulation, especially the Basel II, on bank risk and risk-taking. In order to separate and recognize the efficiency of these effects, the co-effects of many supervisory and regulatory tools together with other relevant factors must be taken into account. The focus of the study is on the effects of asymmetric information and banking procyclicality on the efficiency of the Basel II. This study tries to find an answer, if the Basel II, implemented in 2008, has decreased bank risk in banks of European Union member states. This study examines empirically, if the volatility on bank stock returns have changed after the implementation of the Basel II. Panel data consists of 62 bank stock returns, bank-specific variables, economic variables and variables concerning regulatory environment between 2003 and 2011. Fixed effects regression is used for panel data analysis. Results indicate that volatility on bank stock returns has increased after 2008 and the implementation of the Basel II. Result is statistically very significant and robustness has been verified in different model specifications. The result of this study contradicts with the goal of the Basel II about banking system stability. Banking procyclicality and wrong incentives for regulatory arbitrage under asymmetric information explained in theoretical part may explain this result. On the other hand, simultaneously with the implementation of the Basel II, the global financial crisis emerged and caused severe losses in banks and increased stock volatility. However, it is clear that supervision and regulation was unable to prevent the global financial crisis. After the financial crisis, supervision and regulation have been reformed globally. The main problems of the Basel II, examined in the theoretical part, have been recognized in order to prevent problems of procyclicality and wrong incentives in the future.

Capital structure of Finnish firms – Estimating the effects of firm characteristics on capital structure

One of the most disputable matters in the theory of finance has been the theory of capital structure. The seminal contributions of Modigliani and Miller (1958, 1963) gave rise to a multitude of studies and debates. Since the initial spark, the financial literature has offered two competing theories of financing decision: the trade-off theory and the pecking order theory. The trade-off theory suggests that firms have an optimal capital structure balancing the benefits and costs of debt. The pecking order theory approaches the firm capital structure from information asymmetry perspective and assumes a hierarchy of financing, with firms using first internal funds, followed by debt and as a last resort equity. This thesis analyses the trade-off and pecking order theories and their predictions on a panel data consisting 78 Finnish firms listed on the OMX Helsinki stock exchange. Estimations are performed for the period 2003–2012. The data is collected from Datastream system and consists of financial statement data. A number of capital structure characteristics are identified: firm size, profitability, firm growth opportunities, risk, asset tangibility and taxes, speed of adjustment and financial deficit. A regression analysis is used to examine the effects of the firm characteristics on capitals structure. The regression models were formed based on the relevant theories. The general capital structure model is estimated with fixed effects estimator. Additionally, dynamic models play an important role in several areas of corporate finance, but with the combination of fixed effects and lagged dependent variables the model estimation is more complicated. A dynamic partial adjustment model is estimated using Arellano and Bond (1991) first-differencing generalized method of moments, the ordinary least squares and fixed effects estimators. The results for Finnish listed firms show support for the predictions of profitability, firm size and non-debt tax shields. However, no conclusive support for the pecking-order theory is found. However, the effect of pecking order cannot be fully ignored and it is concluded that instead of being substitutes the trade-off and pecking order theory appear to complement each other. For the partial adjustment model the results show that Finnish listed firms adjust towards their target capital structure with a speed of 29% a year using book debt ratio.

Ammattiliitot makrotaloudessa - voimavara vai rasite?

Tutkielman tavoite oli kuvata ammattiliittojen vaikutusta makrotalouteen. Ammattiliittojen voimaa pyrittiin kuvaamaan työvoiman järjestäytymisasteella muiden mittareiden ollessa kansantalouden inflaatio, työttömyys ja kokonaistuottavuus. Aineisto kattoi 20 OECD-maata, joiden tilastoista koottiin paneeliaineisto. Aineisto kattoi vuodet 1990-2010. Erilaisten liittojärjestelmien vuoksi maat jaettiin neljään eri luokkaan, joita verrattiin keskenään. Paneeliaineistoa tutkittiin kiinteiden vaikutusten sekä satunnaisten vaikutusten mallilla. Tulokset myötäilivät hyvin alan teorioita; tavallisesti vahvat ammattiliitot lisäsivät inflaatiota ja työttömyyttä. Merkittävämmäksi seikaksi nousi järjestäytymisasteen ja kansantalouden tuottavuuden välinen positiivinen korrelaatio. Silti ammattiyhdistysliikkeen kansantaloudellinen merkitys näytti näiden todisteiden valossa olevan negatiivinen, joten taloudellisesti ajatellen ne eivät ole mielekkäitä; jos AY-liikkeelle haluaa löytää perustellun aseman yhteiskunnassa, on se tehtävä jostakin muusta tutkimusnäkökulmasta kuin kansantaloustieteellisestä.

Heat transfer inside internal combustion engine: modelling and comparison with experimental data

The paper is devoted to study specific aspects of heat transfer in the combustion chamber of compression ignited reciprocating internal combustion engines and possibility to directly measure the heat flux by means of Gradient Heat Flux Sensors (GHFS). A one – dimensional single zone model proposed by Kyung Tae Yun et al. and implemented with the aid of Matlab, was used to obtain approximate picture of heat flux behavior in the combustion chamber with relation to the crank angle. The model’s numerical output was compared to the experimental results. The experiment was accomplished by A. Mityakov at four stroke diesel engine Indenor XL4D. Local heat fluxes on the surface of cylinder head were measured with fast – response, high – sensitive GHFS. The comparison of numerical data with experimental results has revealed a small deviation in obtained heat flux values throughout the cycle and different behavior of heat flux curve after Top Dead Center.

Performance Determinants of Renewable Energy Companies

The purpose of this thesis is to identify the Performance Determinants (PD) of Renewable Energy (RE) companies. It analyzes the background of the RE industry while reflecting simultaneous developments in the fossil based industries. I divided the determinants into two groups: market level and firm level and established hypotheses based on the existing literature. Data from public companies was gathered to construct a Panel Data structure. This is then tested by using a Linear Regression with Fixed Effects model. The model specification was efficient at reflecting the analyzed phenomena. My results showed that both market level and firm level determinants are significant in the RE Industry but the firm level determinants had higher explanatory power (R2). The determinants' relationships were found to follow those from the manufacturing industry more than the utilities' industry. Out of the market level determinants Consumer Price Index (CPI), Interest Rates and Oil prices were significant. Out of the firm level determinants Debt to Assets, Net Investments, Cash flows from operations, Sales and Earnings Before Interests and Taxes (EBIT) were significant. I concluded that this information is valuable for key industry players as they can achieve their objectives faster by elaborating better strategies using these results.

Leveraging open access for integrating repository data at Indiana University Libraries

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Explaining the Shifts of International Trade in Pulp and Paper Industry

The pulp and paper industry is currently facing broad structural changes due to global shifts in demand and supply. These changes have significant impacts on national economies worldwide. In this paper, we describe the recent trends in the pulp and recovered paper (RP) production, and estimate augmented gravity models of bilateral trade for chemical pulp and RP exports with panel data. According to our results, there is some variation in the effects of the traditional gravity-model variables between pulp grades and RP. The results imply also that, in comparison to export supply, import demand plays a larger role in determining the volume of exports. Finally, it is evident that Asia, particularly China, is the most important driver of chemical pulp and RP trade: China is hungry for fiber, and must import to satisfy its growing needs. Moreover, the speed of China’s growth in chemical pulp and RP imports has been driving the increased significance of planted forests in the exports of hardwood pulp (BHKP) as well.

Macro- and Microevolution of Languages: Exploring Linguistic Divergence with Approaches from Evolutionary Biology

There are more than 7000 languages in the world, and many of these have emerged through linguistic divergence. While questions related to the drivers of linguistic diversity have been studied before, including studies with quantitative methods, there is no consensus as to which factors drive linguistic divergence, and how. In the thesis, I have studied linguistic divergence with a multidisciplinary approach, applying the framework and quantitative methods of evolutionary biology to language data. With quantitative methods, large datasets may be analyzed objectively, while approaches from evolutionary biology make it possible to revisit old questions (related to, for example, the shape of the phylogeny) with new methods, and adopt novel perspectives to pose novel questions. My chief focus was on the effects exerted on the speakers of a language by environmental and cultural factors. My approach was thus an ecological one, in the sense that I was interested in how the local environment affects humans and whether this human-environment connection plays a possible role in the divergence process. I studied this question in relation to the Uralic language family and to the dialects of Finnish, thus covering two different levels of divergence. However, as the Uralic languages have not previously been studied using quantitative phylogenetic methods, nor have population genetic methods been previously applied to any dialect data, I first evaluated the applicability of these biological methods to language data. I found the biological methodology to be applicable to language data, as my results were rather similar to traditional views as to both the shape of the Uralic phylogeny and the division of Finnish dialects. I also found environmental conditions, or changes in them, to be plausible inducers of linguistic divergence: whether in the first steps in the divergence process, i.e. dialect divergence, or on a large scale with the entire language family. My findings concerning Finnish dialects led me to conclude that the functional connection between linguistic divergence and environmental conditions may arise through human cultural adaptation to varying environmental conditions. This is also one possible explanation on the scale of the Uralic language family as a whole. The results of the thesis bring insights on several different issues in both a local and a global context. First, they shed light on the emergence of the Finnish dialects. If the approach used in the thesis is applied to the dialects of other languages, broader generalizations may be drawn as to the inducers of linguistic divergence. This again brings us closer to understanding the global patterns of linguistic diversity. Secondly, the quantitative phylogeny of the Uralic languages, with estimated times of language divergences, yields another hypothesis as to the shape and age of the language family tree. In addition, the Uralic languages can now be added to the growing list of language families studied with quantitative methods. This will allow broader inferences as to global patterns of language evolution, and more language families can be included in constructing the tree of the world’s languages. Studying history through language, however, is only one way to illuminate the human past. Therefore, thirdly, the findings of the thesis, when combined with studies of other language families, and those for example in genetics and archaeology, bring us again closer to an understanding of human history.