This dissertation examines four specific aspects of capital structure and dividend policy. The first issue concerns the determinants of capital structure dynamics. The primary objective is to examine whether stock returns are important factors in firm???s capital structure choice, and if so, whether this effect is persistent. In so doing, we use a data set which (1) avoids the complexity of tax rates faced by previous studies, (2) we introduce new variables that are unique to Oman, and (3) we distinguish empirically between bank debt and non-bank debt. We find stock returns are a first order determinant of capital structure. Firms do show some tendency to rebalance towards their target capital structure. However, the impact of stock returns dominates the effects of rebalancing. We also find new evidence that firms do take countermeasures to offset changes in their leverage that stem from equity value variations, but do so at a low speed. The next topic studied concerns the ex-dividend day behaviour. We investigate this issue using a unique data set where there are no taxes on dividends and capital gains and stock prices are decimalized. In this economy, any price decline that is smaller than the dividends can not be attributed to taxes and price discreteness. We find that the stock price drops by less than the amount of dividends and there is a significant positive ex-day return. We are able to account for our results using market microstructure models. The third issue investigated is the stock price reaction to dividend announcements. Tax-based signaling models argue that dividends would not have information and be informative if it is not for the higher taxes on dividends relative to capital gains that they apply to shareholders. The absence of personal taxes in Oman presents a valuable opportunity to test this prediction. Our results show that the announcements of dividend increases (decreases) are associated with a stock price increase (decrease) which contradicts the tax-based signaling models. The final chapter analyzes the determinants and stability of dividend policy of financial and non-financial firms. Investigating this issue is important for at least two reasons. First, Omani firms distribute almost 100% of their profits in dividends which led the Capital Market Authority (CMA) to issue a circular (number 12/2003) arguing that firms should retain some of their earnings for ???rainy days???. This allows us understand the characteristics of firms that pay dividends. Second, firms are highly levered mainly through bank loans which render the role of dividends in reducing the agency costs less important. Unlike most previous studies, we include both dividend paying and non-dividend paying firms to avoid a selection bias. We find that there are some common factors that determine dividend policy of both financial and non-financial firms and there are some factors that affect only non-financial firms. We also find that the factors that influence the probability to pay dividends are the same factors that drive the amount of dividends paid for both financial and non-financial firms. We document that non-financial firms adopt a policy of smoothing dividends while financial firms do not have a stable dividend policy.

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Many communities around the country had already been dealing with the problems of increasing and concentrated foreclosures for several years. Thus, the evidence of the social costs of foreclosures will guide policy makers in deciding what policies should be put in many communities that foreclosures have plagued. The objective of this research is to quantify the price-depressing foreclosure effects on existing home sale prices as one of the major social costs for communities. The first methodological goal is to simultaneously quantify the magnitude of the direct and the spillover effects of foreclosures on existing home prices. The second methodological goal is to provide usefulness concerning spatial econometric models in measuring the impact of foreclosures on housing prices. This study was estimated with traditional hedonic and spatial hedonic models specified during two different housing cycles in Phoenix, Arizona, during a strong housing market when prices were up (2005) and a down housing market with falling prices (2008). It has been shown that foreclosures have negative effects on existing home prices in the neighborhood, depending on housing types and cycles. However, the OLS models do not correct for spatial autocorrelation problems and endogeneity that exist in a cross section of house prices and would overestimate absolute values of the coefficients. As alternatives, the maximum likelihood spatial lag or error model controls for spatial autocorrelation but still causes computation obstacles for large data sets and problems of heteroskedasticity in error terms. Thus, the preferred specification is a generalized method of moments (GMM) approach which requires weaker assumptions than the maximum likelihood application and has flexible form to large datasets. As a joint analysis, the most appropriate specification is the general spatial two-stage least-squares (GMM_2SLS) method with HAC (the spatial heteroskedasticity and autocorrelation consistent) variance estimator. These findings provide further evidence that OLS estimates of a coefficient on a foreclosure indicator tend to overstate the direct or indirect foreclosure discount, ignoring spatial effects such as spatial dependence and endogeneity. With regard to the spillover effect of nearby foreclosures on home prices, both foreclosures of single family homes and condos are statistically significant and negatively impact each type of home sale prices. However, the cumulative effects of neighborhood foreclosures are much greater with nonlinear effects in a housing bust year than a housing boom year. Therefore, this study on price-depressing effects of foreclosures emphasizes the importance of the pre-foreclosure step as the beginning of following foreclosure processes, depending on housing types and housing market cycles.

I den här studien analyseras hur Kinas konsumtion av olja påverkas av förändringar i oljepris och inkomst. Resultat visar att deras konsumtion av olja i förhållande till BNP per capita är relativt låg samt att deras fordonskoncentration är låg. År 2004 konsumerade Kina 14 procent mindre olja per capita än vad genomsnittligt land gör vid samma BNP per capitanivå. Fordonskoncentration år 2003 var 25 fordon per 1000 invånare, denna studie visar att om de hade haft en genomsnittlig fordonskoncentration skulle denna siffra varit 40 samma sätt till att vara på Deras ovan nämnda relativt låga fordonskoncentration och konsumtion av olja, kan peka mot att en fortsatt konsumtionsökning. År 2004 var den globala konsumtionen av olja i genomsnitt 81 miljoner fat dagligen (mb/d) och Kinas uppgick till 6.7 mb/d (BPstats ). Ett antal prognoser finns gjorda angående Kinas framtida konsumtion av olja. Enligt EIA 2005, kommer den att uppgå till 12.3 mb/d år 2020 och enligt IEA 2005 till 11.2 mb/d år 2020. Den empiriska undersökningen i denna studie belyser med signifikanta resultat hur Kinas konsumtion av olja påverkas utav pris- och inkomstförändringar. De ekonometriska resultaten i denna studie indikerar att deras konsumtion av olja är mer känslig för inkomst- än prisförändringar. Den långsiktiga inkomstelasticiteten uppmättes i den här studien till 1.317 och den långsiktiga priselasticiteten till -0.633. Med hänvisning till detta och ceteris paribus, kan en inkomstökning på 100 procent över perioden 2005-2020 leda till att Kina år 2020 konsumerar 17.6 mb/d. Således kan prognoserna från EIA (2005) och IEA (2005) vara underestimerade. De inkomst- och priselasticitet som är estimerade i denna studie konfirmerar Dargay och Gatelys resultat från 1994 att ett mindre utvecklat lands konsumtion av olja påverkas mer av förändringar i inkomst än i pris.

This study examines the relationship between stock prices and accounting figures, primarily the book value of equity and earnings, as well as the market perception of accounting choices implemented by companies. Market event studies from late sixties have initiated numerous of researches, and the majority of contemporary results were consistent with strong belief in the market efficiency theory. The book value of equity and earnings have been proved to have the highest explanatory power of future stock prices. Other accounting-related issues, like inventory methods or accounting for business combination, were proven to have reliable impact on the stock prices. Moreover, the cash flow implications triggered by the accounting change are not an indispensable condition to influence the stock price level. Although a great body of research has treated the relationship between accounting choices and stock prices, a clear-cut mechanism is not well specified. The evidence is inconsistent, and the consequences of accounting change are difficult to measure. However, the accounting figures included in financial statements remain the most important measure of the companies’ performance. Due to the economic and technical progress, which considerably modified the structure of companies and the environment in which they operate, further studies are advisable in order to maintain the reliability of accounting figures on significant level.

University of Macau / Faculty of Social Sciences and Humanities / Department of Economics

The efficacy of the 2001 and 2003 Bush tax cuts was a major topic of discussion in the 2010 midterm elections. I investigate the effect of the possible expiration and eventual extension of the dividend tax cut on US stock market performance in 2010 based on the methodology used by Amronin, Harrison and Sharpe (2008). I compare aggregate performance of US common stocks relative to foreign stocks using equity indices, and examine cross-sectional performance amongst US stocks by creating different stock portfolios based on their dividend yield. This comparison is done over two event windows, (1) 20-24 September 2010 and (2) 3-8 December 2010. Consistent with previous studies, I find that the US stock market did respond to negative and positive news on the extension of the Bush-era dividend tax cuts, with stock prices falling and rising, respectively. My findings also suggest that this aggregate effect was probably muted by the redistribution of funds by investors from lower-yield to higher-yield stocks. Unlike in 2003, however, in the post-financial crisis context of 2010, the redistribution seemed to particularly favor stocks with medium-dividend yield, rather than smaller, higher-risk stocks with the highest dividend yield.

This dissertation analyzes the complex relationships between language, immigration, and labor and housing market outcomes. First, I model the urban labor market as segmented by language barriers. The prediction of this segmentation theory is confirmed by Canadian Census data, which allow me to identify a worker's labor market segment by her work language. Second, I explore whether the housing market reflects people's willingness to pay for higher quality social-ethnic interactions. By combining housing transaction data and Census information, I am able to test such a relationship with positive results. Finally, I ask what properties housing price series have if some people have better knowledge of the future immigration/migration flows to a city. Under this setup, the price series become serially correlated and the price volatility varies over time. The model also explains the long-standing price-volume relationship in housing transaction data.

Using seventeen years of data from 1991 to 2008, I derive a pricing model for farmland values. This valuation model is the first using agricultural commodity futures as a proxy for “ex ante” income projections for the crops grown or livestock grazed on United States farmland. While not all inclusive, the model is tested regionally including the Corn Belt, Delta States, Lake States, Mountain, Pacific Northwest, Pacific West and Southeast Regions. Additionally, I test whether interest rate futures contracts have a relationship with farmland values as interest rates have been proven to be a reliable predictor in past research. Farmland capitalization rates and anticipated inflation have hypothesized relationships, but are mainly used as control variables in the study. In general, agricultural commodity futures contracts are a poor predictor of changes in farmland market values. When examining relationships with quarterly percentage change regression models of the included variables, I find the Mountain region provides the most reliable pricing model where both live cattle and Minnesota wheat futures contracts has a positive statistically significant relationships with farmland market values. Also, wheat futures prices have a significant relationship with farmland values in the Corn Belt region. Interest rate futures contracts, farmland capitalization rates and anticipated inflation are not statistically significant in the majority of the regions. As a robustness check, I model the price levels of the variables using Johansen’s cointegration procedure. This time-series econometric methodology provides results in regards to long-run equilibrium relationships between the variables. The results are only slightly better. Corn, orange juice and sugar futures contracts have positive statistically significant relationships with farmland market values in multiple regions. Again, wheat has a statistically significant positive relationship with farmland values in the Corn Belt region. The Mountain region and interest rate futures contracts are not applicable for the cointegration tests as they are not integrated to the order of one.