This paper builds on the study Prices on the Second-hand Market for Swedish Family Housesconducted by Lennart Berg, economist and associate professor emeritus from UppsalaUniversity in 2002. This study attempts to identify inter-and intraregional pricedependencies in Sweden for the second hand market for family houses. The house priceindices used in this econometric analysis commences in 1990:1 and ends in 2018:4 for allregions in accordance to NUTS 2 in Sweden.This thesis models the change of the regional prices for one-and two family houses indicatingthat the metropolitan area of Stockholm contributes predominantly to all other regionsthroughout the country. In addition, the capital city also shows cointegrated relationshipswith all regions although not the contrary. Shocks to the housing market of Stockholmindicate that Gothenburg, the Western region and Malmö are affected contemporaneouslyfollowed by the other regions nationwide with a certain time lag leading to say that thecontribution and influence of the capital city´s house price development leads the pricedevelopment throughout the country, Sweden. / Detta examensarbete ligger till grund av den tidigare studien Prices on the Second-handMarket for Swedish Family Houses av Lennart Berg, nationalekonom och professor emerituspå Uppsala Universitet, 2002. Denna studie har som mål att finna de inter-och intraregionala pris förhållanden i Sverige på den inhemska andrahandsmarknaden för en-och tvåfamiljhus. Med hjälp av ekonometriska analyser har fastighetsprisindex använts i rapportenmellan år 1990:1 till 2018:4 för samtliga regioner i landet enligt indelning av NUTS 2.Denna uppsats skattar de regionala prisförändringar för en-och två familjehus därindikationer tyder på att Stockholms län verkar vara prisledande i relation till alla andraregioner och storstadsområden i Sverige. Därutöver, visar det sig att huvudstaden harkointegrerande samband med resten av landets regioner dock ej tvärtom. Simuleradeekonomiska chocker på Stockholms län visar att att Stor-Göteborg, Västsverige och Stor-Malmö är påverkade samtidigt med hänsyn till tid följd av de resterande regionerna med ettvisst lag. Detta kan tyda på att Stockholms regionala utveckling samt prispåverkan lederprisutvecklingen i landet.

<p>This dissertation consists of four self-contained essays.</p><p>Essay I (with Cecilia Enström Öst) investigates whether housing allowance affects recipients’ tenure choice in Sweden. A two-stage conditional maxi-mum likelihood probit (2SCMLP) model is applied in a panel data setting to simultaneously control for individual heterogeneity, state dependence and endogeneity. The empirical study is based on administrative data of housing allowance recipients between the years 1994 and 2002. Our results indicate that the housing allowance positively affects recipients’ homeownership propensity in Sweden. </p><p>Essay II investigates whether the Swedish housing allowance system creates dependence on welfare in recipients. Using longitudinal data from Swedish micro database-LINDA, this paper found that there is no evidence of nega-tive duration dependence among the Swedish housing allowance spells. This finding is consistent across different model specifications and various con-trols of the heterogeneity issue. </p><p>Essay III analyzes the impacts of the 1997 reform of Swedish housing al-lowance system on affected recipients’ exit hazards using the DD (differ-ence-in-difference) estimation strategy. This paper found strong evidence that the 1997 reform positively shifted up the conditional exiting probability of the couple with children recipient group, and the estimated magnitude of impact is sizable.</p><p>Essay IV extends the VECM (Vector Error Correction Cointegration Model) and PT (permanent-transitory) variance decomposition framework proposed by Lettau & Ludvigson (2004) to a situation in which total wealth is disag-gregated into housing wealth and financial wealth. The empirical studies are based on the Swedish aggregate quarterly data spanning from 1980q1 to 2004q4. We found strong statistical evidence that the movements of total consumption expenditures, disposable income, housing wealth and financial wealth are tied together. It is also shown that the movements of housing wealth in Sweden contain a large proportion of transitory component. </p>

This dissertation consists of four self-contained essays. Essay I (with Cecilia Enström Öst) investigates whether housing allowance affects recipients’ tenure choice in Sweden. A two-stage conditional maxi-mum likelihood probit (2SCMLP) model is applied in a panel data setting to simultaneously control for individual heterogeneity, state dependence and endogeneity. The empirical study is based on administrative data of housing allowance recipients between the years 1994 and 2002. Our results indicate that the housing allowance positively affects recipients’ homeownership propensity in Sweden. Essay II investigates whether the Swedish housing allowance system creates dependence on welfare in recipients. Using longitudinal data from Swedish micro database-LINDA, this paper found that there is no evidence of nega-tive duration dependence among the Swedish housing allowance spells. This finding is consistent across different model specifications and various con-trols of the heterogeneity issue. Essay III analyzes the impacts of the 1997 reform of Swedish housing al-lowance system on affected recipients’ exit hazards using the DD (differ-ence-in-difference) estimation strategy. This paper found strong evidence that the 1997 reform positively shifted up the conditional exiting probability of the couple with children recipient group, and the estimated magnitude of impact is sizable. Essay IV extends the VECM (Vector Error Correction Cointegration Model) and PT (permanent-transitory) variance decomposition framework proposed by Lettau &amp; Ludvigson (2004) to a situation in which total wealth is disag-gregated into housing wealth and financial wealth. The empirical studies are based on the Swedish aggregate quarterly data spanning from 1980q1 to 2004q4. We found strong statistical evidence that the movements of total consumption expenditures, disposable income, housing wealth and financial wealth are tied together. It is also shown that the movements of housing wealth in Sweden contain a large proportion of transitory component.

This dissertation consists of three essays wherein tools of financial econometrics are used to study the three aspects of farmland valuation puzzle: short-term boom-bust cycles, overpricing of farmland, and inconclusive effects of direct government payments. Essay I addresses the causes of unexplained short-term boom-bust cycles in farmland values in a dynamic land pricing model (DLPM). The analysis finds that gross return rate of farmland asset decreases as the farmland asset level increases, and that the diminishing return function of farmland asset contributes to the boom-bust cycles in farmland values. Furthermore, it is mathematically proved that land values are potentially unstable under diminishing return functions. We also find that intertemporal elasticity of substitution, risk aversion, and transaction costs are important determinants of farmland asset values. Essay II examines the apparent overpricing of farmland by decomposing the forecast error variance of farmland prices into forward looking and backward looking components. The analysis finds that in the short run, the forward looking Capital Asset Pricing Model (CAPM) portion of the forecast errors are significantly higher in a boom or bust stage than in a stable stage. This shows that the farmland market absorbs economic information in a discriminative manner according to the stability of the market, and the market (and actors therein) responds to new information gradually as suggested by the theory. This helps to explain the overpricing of farmland, but this explanation works primarily in the short run. Finally, essay III investigates the duel effects of direct government payments and climate change on farmland values. This study uses a smooth coefficient semi-parametric panel data model. The analysis finds that land valuation is affected by climate change and government payments, both through discounted revenues and through effects on the risk aversion of land owners. This essay shows that including heterogeneous risk aversion is an efficient way to mitigate the impacts of misspecifications in a DLPM, and that precipitation is a good explanatory variable. In particular, precipitation affects land values in a bimodal manner, indicating that farmland prices could have multiple peaks in precipitation due to adaption through crop selection and technology alternation.

The worldwide economic downturn and recession in the second half of 2008 were mainly the result of the crises that influenced the world‟s financial markets. After the financial crisis, the extended period of rapid credit growth that was driven by asset price increases, especially property prices, came to an end. This identified two problems central to the theme of this study. The first problem was illustrated through the recent crisis, which showed that problems in the financial sector have a potentially destabilising effect on the economy, to such an extent that they also affect the real economy. The second problem highlighted by the recent financial crisis pertains to the current macroeconomic framework, which indicates policy failure to detect and deal with financial sector instabilities. The objective of this study was to develop a framework in which the influence that rapidly growing credit and asset prices have on financial stability could be determined. Two distinct empirical models were estimated in order to reach the main objective of this study. The first model established the influence that asset prices and credit growth have on the real economy. It concluded that a long-run relationship exists between inflation, real GDP, credit extended to the private sector, house prices and share prices. A bi-directional relationship was found between house and share price, which indicates the interdependence of asset prices in SA. The transmission channels assume that credit is influenced by interest rates, but the results also found that interest rates are largely influenced by credit. The second model determined the influence of asset prices and credit on financial stability. A significant long-run relationship was found between financial stability, share and house prices, and between share prices, credit and financial stability. It was found that credit and share prices can be used to signal financial instability, and share prices can help to determine future credit extended to the private sector. In addition, the empirical analysis indicated that a credit market squeeze will be experienced after a decrease in financial stability. Lastly, credit extended will increase as a result of shock to house and share prices and financial stability will decrease when there is a shock to share and house prices. / MCom (Economics), North-West University, Potchefstroom Campus, 2013

The worldwide economic downturn and recession in the second half of 2008 were mainly the result of the crises that influenced the world‟s financial markets. After the financial crisis, the extended period of rapid credit growth that was driven by asset price increases, especially property prices, came to an end. This identified two problems central to the theme of this study. The first problem was illustrated through the recent crisis, which showed that problems in the financial sector have a potentially destabilising effect on the economy, to such an extent that they also affect the real economy. The second problem highlighted by the recent financial crisis pertains to the current macroeconomic framework, which indicates policy failure to detect and deal with financial sector instabilities. The objective of this study was to develop a framework in which the influence that rapidly growing credit and asset prices have on financial stability could be determined. Two distinct empirical models were estimated in order to reach the main objective of this study. The first model established the influence that asset prices and credit growth have on the real economy. It concluded that a long-run relationship exists between inflation, real GDP, credit extended to the private sector, house prices and share prices. A bi-directional relationship was found between house and share price, which indicates the interdependence of asset prices in SA. The transmission channels assume that credit is influenced by interest rates, but the results also found that interest rates are largely influenced by credit. The second model determined the influence of asset prices and credit on financial stability. A significant long-run relationship was found between financial stability, share and house prices, and between share prices, credit and financial stability. It was found that credit and share prices can be used to signal financial instability, and share prices can help to determine future credit extended to the private sector. In addition, the empirical analysis indicated that a credit market squeeze will be experienced after a decrease in financial stability. Lastly, credit extended will increase as a result of shock to house and share prices and financial stability will decrease when there is a shock to share and house prices. / MCom (Economics), North-West University, Potchefstroom Campus, 2013

Submitted by Ulisses Nehmi (ulisses@nehmi.com.br) on 2017-12-22T17:42:27Z No. of bitstreams: 1 Dissert_MPE_Ulisses_2017.12.pdf: 2808696 bytes, checksum: fe4dbd86f710e7d09cbb1705853aba42 (MD5) / Approved for entry into archive by Thais Oliveira (thais.oliveira@fgv.br) on 2017-12-22T17:51:45Z (GMT) No. of bitstreams: 1 Dissert_MPE_Ulisses_2017.12.pdf: 2808696 bytes, checksum: fe4dbd86f710e7d09cbb1705853aba42 (MD5) / Made available in DSpace on 2017-12-23T15:56:54Z (GMT). No. of bitstreams: 1 Dissert_MPE_Ulisses_2017.12.pdf: 2808696 bytes, checksum: fe4dbd86f710e7d09cbb1705853aba42 (MD5) Previous issue date: 2017-12-15 / Muitos estudos sobre a Estrutura a Termo das Taxas de Juros (ETTJ) focam na análise de um único país, geralmente uma economia desenvolvida. São raros os estudos que avaliam as características das curvas de juros para um conjunto de países desenvolvidos, e ainda mais raros os estudos que avaliam essas características para países emergentes. Este estudo parametrizou a ETTJ de 19 economias por um período de 10 anos, divididas entre economias desenvolvidas e emergentes, identificando as principais características que definem cada grupo, algumas das quais se revelaram contraintuitivas. A parametrização das curvas de juros também foi utilizada para remover o ruído dos dados originais, o que permitiu uma análise mais precisa dos fatores que explicam suas variâncias. Com isso, foram encontradas evidências de diferenças relevantes no peso dos fatores nível, inclinação e curvatura na explicação das variações na ETTJ para os países desenvolvidos em relação aos países emergentes. / Many studies on Term Structure of Interest Rates (TSIR) focus on the analysis of a single country, usually a developed economy. Seldom do studies evaluate the features of yield curves for a set of developed countries, and even more rarely do studies evaluate these features for emerging countries. The present study evaluates the parametric TSIR of 19 economies over a period of 10 years, grouped into two distinct sets: developed and emerging economies. It identifies the main features, some of which have proved counterintuitive, that define each group. The parameterization of the yield curves was also used to removed noise from the original data, which allowed for a more accurate analysis of the factors that explain its variances. Evidence of relevant differences in weights for the level, slope and curvature factors were found, which explain the variations in the TSIR of developed countries relative to emerging countries.

A number of developing countries have been on a quest to attract foreign direct investment (FDI) with the intention of increasing capital inflow through technological spillovers and transfer of managerial skills. FDI can increase economic growth and development of a country by creating employment, and by doing so, increasing economic activity that will lead to economic growth. South Africa is one of the economies that strive to attract more FDI inflows into the country to be able to improve its economy, and the country has adopted policies that drive the motive to attract FDI inflows. This study investigated the effect of FDI on sectoral growth over the period 1970–2014. The purpose was to find out where in the three key sectors of South Africa FDI is more significant. The review of theoretical and empirical literature on FDI revealed that FDI has a diverse effect on economic growth, both in developed and developing countries. Theoretical literature analysed the behaviour of multinational firms and the motive behind multinationals investing in foreign countries. According to Dunning (1993), firms have four motives to decide to produce abroad, namely natural resource-seeking, market-seeking, efficiency-seeking and strategic asset-seeking. Empirical studies on sectors show that FDI inflows affect different sectors in different ways, and that the agricultural sector does not usually gain from FDI inflows, whereas subsectors in the industry and services sector grow from receiving FDI inflows. Sectoral analysis revealed that the services sector receives more FDI inflows, when compared to the agriculture and industry sector. The study followed an econometric analysis technique to test the effect of FDI inflows on the agriculture, industry and services sectors. The augmented Dickey–Fuller and Phillips–Perron tests were used to test for unit root. Both tests revealed that variables were not stationary at level, but that they become stationary at first difference. Vector autoregressive (VAR) models were estimated, and four types of diagnostic tests were performed on them to check the fitness of the models. The tests showed that residuals of the estimated VARs were robust and well behaved. The Johansen cointegration test suggested there is cointegration and that there is a long-run relationship between variables. Following the existence of cointegration, the estimated Vector error correction model (VECM) results showed that FDI has a significant effect on the services and industry sector, but has a negative effect on the agricultural sector. Impulse response analysis results revealed the correct signs, and confirmed the VECM results. FDI inflows explain a small percentage of growth in agriculture and industry, but a sizable and significant percentage in the services sector. / Economics / M. Com. (Economics)

This paper analyzes and distinguishes the role and importance of the shocks related to the aggregate demand and aggregate supply on the behavior of the Peruvian inflation during the period 1997:1-2009:2. We use the methodology based on structural vector autoregressive (SVAR) models using a long-run identification based on Blanchard and Quah (1989) which allows to obtain the historical decomposition of the annual inflation. Unlike Salas (2009), this paper uses a more simple model of aggregate demand and aggregate supply, and a larger sample. The results show that the behavior of inflation was largely explained for shocks related to the aggregate demand side in comparison with aggregate supply shocks. Furthermore, the results of the variance decomposition of the prediction error show that in the short and long term, the shocks of the demand side explain around 70% and 60% of the movements of the inflation. The results are robust to the inclusion of different variables in the set of information. / Este documento distingue y explica el rol y la importancia de los choques de demanda y oferta agregada en el comportamiento de la inflación peruana durante el periodo 1997:1-2009:2. Para esto se utiliza la metodología de Vectores Autoregresivos Estructurales (SVAR, por sus siglas en inglés) con una descomposición de largo plazo propuesta por Blanchard y Quah (1989), lo que permite obtener la descomposición histórica de la inflación anual. A diferencia de Salas (2009), el presente trabajo se basa en un modelo simple de demanda y oferta agregada, y una muestra más amplia. Los resultados muestran que el comportamiento de la inflación obedeció en mayor medida a choques de demanda agregada en comparación con los choques de oferta agregada. Los resultados de la descomposición de la varianza del error de predicción muestran que, en el corto y largo plazo, los choques de demanda agregada explican alrededor del 70% y 60% de los movimientos de la inflación. Los resultados son robustos a la inclusión de diferentes variables dentro del conjunto de información.

Submitted by Alexandre Pignanelli (alexandre.pignanelli@fgv.br) on 2012-09-14T04:50:22Z No. of bitstreams: 1 Tese Alexandre Pignanelli.pdf: 10725491 bytes, checksum: 294362f3f6f0edd963b319bb62eb292c (MD5) / Approved for entry into archive by Suzinei Teles Garcia Garcia (suzinei.garcia@fgv.br) on 2012-09-14T11:31:58Z (GMT) No. of bitstreams: 1 Tese Alexandre Pignanelli.pdf: 10725491 bytes, checksum: 294362f3f6f0edd963b319bb62eb292c (MD5) / Made available in DSpace on 2012-09-14T11:56:44Z (GMT). No. of bitstreams: 1 Tese Alexandre Pignanelli.pdf: 10725491 bytes, checksum: 294362f3f6f0edd963b319bb62eb292c (MD5) Previous issue date: 2011-12-21 / The mechanisms leading to superior performance and the factors that explain them are subjects of interest to many areas in business research. The variance decomposition of performance has been used for such purposes, initially trying to understand the contribution of idiosyncratic organizational factors (firm effect) and factors related to the economic sector (industry effect); more recently other factors have gained interest, such as the contributions of corporation and country to firm performance. This doctoral thesis has introduced a new factor in studies of variance decomposition of performance: the supply chain effect, quantifying the influence of affiliation to a given supply chain to firm performance. Another contribution of this thesis is a comprehensive panorama of the structure of performance variance in Brazil, expanding previous research in terms of sample size, a more suitable method of analysis (multilevel or hierarchical linear models) and performance dimensions used. The empirical analysis considered indicators of profit and growth, with the broader sample containing 592,905 observations from 77,468 Brazilian firms and 485 industries, in a period of 10 years. Data were obtained from annual structural economic surveys conducted by Brazilian Institute of Geography and Statistics (IBGE). Three-levels hierarchical linear models, with observations of performance, firms and industries, showed that the firm effect accounts for the greatest portion of explained variance; these models also pointed to peculiar characteristics of the Brazilian context, such as the differences in the structure of variance when the different sectors are analyzed separately, mainly in terms of intensity of the industry effect – more relevant, for example, for service firms than for firms from other industries – and the differences in the structure of variance for the various regions of Brazil, being firms from the North, Northeast and Midwest regions more dependent on industry’s contribution to their performance than firms from the South and Southeast. With the introduction of a fourth level – the supply chain – to the model, it was found that the magnitude of the supply chain effect reached 15% to 25% of the explained variability, measured by the square root of the variance components, representing about 50% to 90% of the industry effect magnitude. Beyond highlighting the importance of supply chain management, the findings suggest a new understanding of the industry effect, as they indicate that the benefits traditionally attributed to the industry are partly resulting from the firm affiliation to a supply chain, and not only from the similarity of activities it shares with other firms in the same industry. / Os mecanismos que levam ao desempenho superior e, por consequência, os fatores que os explicam, são focos de várias áreas de pesquisa em Administração de Empresas. A decomposição da variabilidade do desempenho vem sendo utilizada para esse fim, inicialmente procurando entender a contribuição de fatores intrínsecos às organizações (efeito empresa) e de fatores relacionados ao setor econômico (efeito setor); mais recentemente outros fatores ganharam interesse, como é o caso das contribuições da corporação e do país para o desempenho. Esta tese introduziu um novo fator aos estudos de decomposição da variabilidade do desempenho: o efeito cadeia de suprimentos, quantificando a influência da afiliação a uma determinada cadeia para o desempenho da empresa. Outra contribuição desta tese é o amplo mapeamento da estrutura de variância de desempenho das empresas brasileiras, expandindo pesquisas anteriores em termos de tamanho de amostra, método de análise mais adequado (modelagem multinível) e dimensões de desempenho utilizadas. As análises empíricas consideraram indicadores de lucro e de crescimento, com a amostra mais ampla contendo 592.905 observações de 77.468 empresas brasileiras e 485 setores de negócios, em um período de 10 anos. Os dados foram obtidos das bases de dados das pesquisas econômicas estruturais do Instituto Brasileiro de Geografia e Estatística (IBGE). Modelos de 3 níveis – observações de desempenho, empresas e setores – mostraram que o efeito empresa individual responde pela maior parcela da variância do desempenho; esses modelos também apontaram para características peculiares da realidade brasileira, como as diferenças das estruturas de variância quando os diversos setores são analisados separadamente, principalmente em termos da intensidade do efeito setor – mais relevante, por exemplo, para as empresas de serviços do que para as empresas dos demais setores – e como as diferenças nas estruturas de variância para as diversas regiões do Brasil, sendo as empresas das regiões Norte, Nordeste e Centro-Oeste mais dependentes da contribuição do setor para seu desempenho do que as empresas da região Sul e Sudeste. Ao se introduzir um quarto nível – a cadeia de suprimentos – ao modelo, foi possível identificar que a magnitude do efeito cadeia alcança entre 15% a 25% da variabilidade explicada, medida pela raiz quadrada dos componentes de variância, representando cerca de 50% a 90% da magnitude do efeito setor. Além de evidenciar a importância da gestão das cadeias de suprimentos, os achados apontam para uma nova compreensão do efeito setor, já que indicam que os benefícios tradicionalmente atribuídos ao setor econômico são em parte decorrentes da afiliação da empresa a uma determinada cadeia, e não à similaridade das atividades que ela compartilha com outras empresas do mesmo setor.