Mergers and acquisitions remain a constant feature of both the local and international markets, but little is definitely know about what determinants of aggregate merger activityThe aim of this research report is to evaluate the dynamic relationship between a selected number of determinants and aggregate merger activity. We limited our selection of determinants to either macroeconomic or market factors, and limited our acquirers listed on the Johannesburg Stock Exchange.We defined aggregate merger activity using three measures, namely, quarterly deal frequency, quarterly deal value and a relative measure, which took the ratio of deal value over the JSE All Share Index. We utilised Gross Domestic Product, the Repurchase Rate, Consumer Price Index (CPI) and Producer Price Index (PPI) as our macroeconomic variables. Our market variables were the JSE All Share Index, the All Bond Index and the USD/ZAR Foreign Exchange Rate. Employing the appropriate data transformations, unit root, regression analysis and cointegration tests we were able to statistically test for the hypothesized relationships.Results indicated that only the Repurchase Rate was applicable in explaining the variation in the deal frequency variable, while none of the chosen determinants were significant in explaining the variation in the deal value and relative deal value measures. Overall, we found in all three cases that the fitted regression model did not explain the variation in our aggregate merger measure well.On a long-term equilibrium basis, we found that the All Bond Index and CPI were cointegrated with the deal frequency measure. The deal value measure had a long-term equilibrium relationship with the JSE All Share Index, while the relative deal value measure had a long term equilibrium relationship with the All Bond Index, CPI and PPI / Dissertation (MBA)--University of Pretoria, 2012. / Gordon Institute of Business Science (GIBS) / unrestricted

This study investigates the impact macroeconomic factors have on corporate capital structure in Sweden. We use a panel data analysis of unbalanced data for the sample period, 2005-2014. While previous research has shown that key factors internal to the firm are highly correlated with leverage, such as profitability, asset tangibility and firm size, we add external factors and test for economic growth, inflation, interest rates, corporate tax rates, and exchange rates. Our models do not present any substantial explanatory power for the relationship between the macroeconomic environment and different leverage ratios. This study finds some support for certain indicators, although not consistent across ratios.

Recent nancial crises have highlighted the sensitivity and vulnerability of nancial markets to in ation, which reduces the value of money and a ects the net returns of nancial instruments. In response to this, investors who are concerned with maintaining their investment's purchasing power rather than its market value are resorting to in ation linked (IL) products to hedge their in ation risk. Consequently, the in ation market has been rapidly growing for the last decade and has further great potential growth worldwide. It is highly probable that in ation linked derivatives will eventually be as common as conventional products. Another cause of the in ation market boost is the growing extension of the time frame of nancial transactions, which has generated an increase in in ation expectation; since 1980 the average time to maturity of long-dated transactions went from one decade to three decades. This is, in part, due to the ageing population in the developed world. This research investigates some alternative models in order to improve the match between model prices and observed prices in the American and South African in ation markets. It takes into account the relative illiquidity of IL products. The main tools used are L evy distributions, macroeconomic factors, no-arbitrage and pricing kernel models. L evy processes can replicate the behaviour of the return innovations of a wide range of nancial securities. Adding a stochastic time change to the L evy process randomises the market clock, thus generating stochastic volatilities, higher stochastic return moments and eventually stochastic skewness. These are observed stylised facts most conventional models do not achieve. Moreover, in contrast to the hidden factor approach, each L evy process component and its stochastic time change can readily be assigned an economic meaning. This explicit economic mapping facilitates the interpretation of current models and provides a more intuitive approach to building new models that capture other observed behaviours. Finally, L evy processes also provide tractable formulas for derivative pricing and market estimations. In general, in ation is a consequence of macroeconomic factors. Exogenous dynamics of the most signi cant of these factors are used to deduce the endogenous in ation dynamics in some of the considered models. In these cases, the calibration of the pricing kernel models requires little historical data on IL derivatives. In fact, the required macroeconomic historical data is easily available because of the current national and international legislation.

Buying a house is for most people the biggest investment they will ever make. A lot of factors are taken in to consideration when looking for the perfect house; location, size, what state it is in and so forth. But since most people’s budgets are limited, the price is probably the most important aspect in the decision making process of buying a house. It is therefore highly interesting to note that since 1981, house prices in Sweden have increased with almost 400 percent. This thesis examines the relationship between small house prices and macroeconomic factors in the Stockholm region during the period 1991 to 2007. By using macro economic theories complemented by data for all Stockholm’s municipalities in a OLS regression, the thesis will explain how the variables affects the small house prices in a boom, recession and over time. The results and analysis reveals that as house prices rises, people tend to increase their spending on interest costs and vice versa if the prices falls. Furthermore, results show that in a boom, an existence of speculation is contributing to the rise while convergence is an important factor in a recession. The most important conclusion from this thesis is the fact that the influence of macroeconomic variables on house prices differs significantly, depending on if the economy is in a recession or a boom. Finally, the influence on the economy that the house- and real estate market possesses cannot be underestimated with its important effect on the credit market, inflation and asset market. / Husköp är för de flesta människor deras livs största investering och det är därför många faktorer som först måste vägas in varav den viktigaste förmodligen är priset. Huspriserna i Sverige har sedan 1981 nästan fyrdubblats, en utveckling som är mycket kraftigare än inflationen samma tid. Den här kandidatuppsatsen avser att undersöka Stockholmregionens småhuspriser åren 1981-2007 och dess relation till makroekonomiska faktorer. Genom att använda en OLS regression med insamlad data för Stockholms alla kommuner och makroekonomiska teorier, visar vi hur utvalda makroekonomiska variabler påverkar småhuspriserna generellt, i hög- samt lågkonjunktur. Resultat och analys visar att om småhuspriserna går upp är tenderar Stockholms befolkning att lägga en större del av deras inkomst på räntekostnader och tvärtom när priserna går ner. En psykologisk aspekt har en viktig del i dessa upp och nedgångar, i en uppgång startar en spekulationsperiod då människor vill vara en del ägandet i den uppåtgående husmarknad medans i en nergång skapas en sorts konvergens och en rad faktorer påverkar varandra i en spiralliknande nedåt trend. Denna trend kan förklaras i DiPasquales och Wheatons assets market model där det positiva förhållandet mellan marknader som hyresmarknaden, kreditmarknaden, byggmarknaden och tillgångsmarknaden står i fokus. Den viktigaste slutsatsen i uppsatsen är att makroekonomiska faktorer påverkar småhuspriserna helt olika beroende på om ekonomin är i en hög eller lågkonjunktur. Slutligen bör nämnas hur viktigt hus- och fastighetsmarknaden är för en ekonomi genom dess påverkan på kreditmarknaden och inflationen.

Investments in R&D activities are essential to firms. Decisions to increase or decrease R&D investments may rely according to changes in macroeconomic factors. The purpose of this paper is: to examine how firms in the industries; manufacturing computers, electronics and optics and manufacturing electrical equipment, have increased or decreased their R&D investments, in conjunction with macro factors during the 2000s. The sample is 49 Swedish firms. This paper is based on quantitative firm-level panel data on R&D activity investments and aggregated quantitative macro-level data on macro factors. The firm-level panel data set has been put together completely from scratch, using collected and transformed raw data. Using a logistic regression model, the results show that macro factors do affect R&D investments on a micro-level, to some extent. Further, the results show that change in macro factors does to a greater extent, affect decreases in R&D investments than increases in R&D investments. The process of increase and decrease of R&D investment should be considered as two different dynamic processes. Increase and decrease do not follow the same pattern, thus a decrease of R&D investments is a more explicit decision than a decision to increase R&D investments.

Affine term structure models (ATSMs) are known to have a trade-off in predicting future Treasury yields and fitting the time-varying volatility of interest rates. First, I empirically study the role of macroeconomic variables in simultaneously achieving these two goals under affine models. To this end, I incorporate a liquidity demand theory via a measure of the velocity of money into affine models. I find that this considerably reduces the statistical tension between matching the first and second moments of interest rates. In terms of forecasting yields, the models with the velocity of money outperform among the ATSMs examined, including those with inflation and real activity. My result is robust across maturities, forecasting horizons, risk price specifications, and the number of latent factors. Next, I incorporate latent macro factors and the spread factor between the short-term Treasury yield and the federal funds rate into an affine term structure model by imposing cross-equation restrictions from no-arbitrage using daily data. In doing so, I identify the highfrequency monetary policy rule that describes the central bank's reaction to expected inflation and real activity at daily frequency. I find that my affine model with macro factors and the spread factor shows better forecasting performance.

<p> </p><p>Buying a house is for most people the biggest investment they will ever make. A lot of factors are taken in to consideration when looking for the perfect house; location, size, what state it is in and so forth. But since most people’s budgets are limited, the price is probably the most important aspect in the decision making process of buying a house. It is therefore highly interesting to note that since 1981, house prices in Sweden have increased with almost 400 percent.</p><p>This thesis examines the relationship between small house prices and macroeconomic factors in the Stockholm region during the period 1991 to 2007. By using macro economic theories complemented by data for all Stockholm’s municipalities in a OLS regression, the thesis will explain how the variables affects the small house prices in a boom, recession and over time.</p><p>The results and analysis reveals that as house prices rises, people tend to increase their spending on interest costs and vice versa if the prices falls. Furthermore, results show that in a boom, an existence of speculation is contributing to the rise while convergence is an important factor in a recession. The most important conclusion from this thesis is the fact that the influence of macroeconomic variables on house prices differs significantly, depending on if the economy is in a recession or a boom. Finally, the influence on the economy that the house- and real estate market possesses cannot be underestimated with its important effect on the credit market, inflation and asset market.</p><p> </p> / <p> </p><p>Husköp är för de flesta människor deras livs största investering och det är därför många faktorer som först måste vägas in varav den viktigaste förmodligen är priset. Huspriserna i Sverige har sedan 1981 nästan fyrdubblats, en utveckling som är mycket kraftigare än inflationen samma tid.</p><p>Den här kandidatuppsatsen avser att undersöka Stockholmregionens småhuspriser åren 1981-2007 och dess relation till makroekonomiska faktorer. Genom att använda en OLS regression med insamlad data för Stockholms alla kommuner och makroekonomiska teorier, visar vi hur utvalda makroekonomiska variabler påverkar småhuspriserna generellt, i hög- samt lågkonjunktur.</p><p>Resultat och analys visar att om småhuspriserna går upp är tenderar Stockholms befolkning att lägga en större del av deras inkomst på räntekostnader och tvärtom när priserna går ner. En psykologisk aspekt har en viktig del i dessa upp och nedgångar, i en uppgång startar en spekulationsperiod då människor vill vara en del ägandet i den uppåtgående husmarknad medans i en nergång skapas en sorts konvergens och en rad faktorer påverkar varandra i en spiralliknande nedåt trend. Denna trend kan förklaras i DiPasquales och Wheatons assets market model där det positiva förhållandet mellan marknader som hyresmarknaden, kreditmarknaden, byggmarknaden och tillgångsmarknaden står i fokus. Den viktigaste slutsatsen i uppsatsen är att makroekonomiska faktorer påverkar småhuspriserna helt olika beroende på om ekonomin är i en hög eller lågkonjunktur. Slutligen bör nämnas hur viktigt hus- och fastighetsmarknaden är för en ekonomi genom dess påverkan på kreditmarknaden och inflationen.</p><p> </p>

Submitted by Marilene Donadel (marilene.donadel@unioeste.br) on 2018-06-04T17:18:50Z No. of bitstreams: 1 Erivelto_Hoc_2017.pdf: 1551646 bytes, checksum: 5caa1e5c67d76220b03002578c8d0efb (MD5) / Made available in DSpace on 2018-06-04T17:18:50Z (GMT). No. of bitstreams: 1 Erivelto_Hoc_2017.pdf: 1551646 bytes, checksum: 5caa1e5c67d76220b03002578c8d0efb (MD5) Previous issue date: 2017-06-06 / Agriculture is a sector that has been presenting a significant importance for the Brazilian economy, since it has contributed significantly to the generation of employment and income to the country. However, the internal economic difficulties caused by high interest rates, exchange rate volatility, low volumes of credit in addition to the inflationary process and the lack of fiscal control seen in some periods, provided great challenges for Brazilian agriculture, mainly during the 1980s and 1990s. The performance of this sector has always been linked to a wide range of factors, such as investments in research, the adoption of new technologies, rural entrepreneurship and government support through some economic policies, such as fiscal, monetary / credit and exchange policies - in addition to the specific conditions of the sector itself. Before this scenario, in order to understand some of the macroeconomic factors that influenced the performance of Brazilian agriculture, the relations between rural credit, exchange rate, interest rate, price index received by rural producers and agriculture and livestock farming GDP between 1995 and 2015. In order to obtain empirical answers, a Vector Auto Regressive (VAR) model was used, which demonstrated that rural credit, the price index and the interest rate were the variables that influenced the performance of this sector during the analyzed period. / A agropecuária é um setor que vem apresentando significativa importância para a economia brasileira, pois tem contribuído expressivamente com a geração de emprego e renda ao país. No entanto, as dificuldades econômicas internas ocasionadas pelas elevadas taxas de juros, pela volatilidade cambial, pelos baixos volumes de crédito além do processo inflacionário e o descontrole fiscal visto em alguns períodos, proporcionaram grandes desafios para a agropecuária brasileira, principalmente durante as décadas de 1980 e 1990.O desempenho deste setor sempre esteve ligado aos mais diversos fatores – como os investimentos em pesquisas, a adoção de novas tecnologias, ao empreendedorismo rural e o apoio governamental por meio de algumas políticas econômicas, tais como políticas fiscais, monetárias/creditícias e cambiais – além das condições específicas do próprio setor. Diante desse cenário, com objetivo de compreender alguns dos fatores macroeconômicos que influenciaram no desempenho da agropecuária brasileira, foram analisadas as relações entre o crédito rural, a taxa de câmbio, a taxa de juros, o índice de preços recebidos pelos produtores rurais e o PIB da agropecuária entre os anos de 1995 a 2015.Visando obter respostas empíricas, utilizou-se um modelo de Vetor Auto Regressivo (VAR), o qual demonstrou que o crédito rural, o índice de preços e a taxa de juros foram as variáveis que mais influenciaram o desempenho deste setor durante o período analisado.

This thesis investigates to what extent macroeconomic factors influence real estate stock prices before and after the outbreak of the financial crisis in 2007. This is carried out by examining the securitized real estate markets in Sweden and Switzerland by using descriptive statistics. Bivariate regressions are conducted for the macroeconomic factors; all share stock index, exchange rates, unemployment, inflation, term structure, money supply and real GDP per capita, to examine the marginal effect of each variable. The indexed developments and volatilities of each variable and correlations to the OMXS Real Estate and WUPIX-A are compiled to further facilitate an analysis. The results show that the macroeconomic effects on real estate stock prices differ among small economies and are inconsistent in a pre-crisis and crisis period. Solely theoretical aspects are not sufficient to describe the varying conditions in the financial markets, which have to be scrutinized in a wider economic context. Those factors that show some regularity in the relation to the real estate markets are all share indices, term structure and real GDP per capita.

The flow of foreign direct investment (FDI) into a country can benefit both the investing entity (the home country) and the host country. The determinants of FDI are a highly discussed topic, with various determinants being analysed and discussed over time.  Multiple research papers focus on the determinants of the host country, which try to identify the most important factors that make countries attractive to investment from abroad. This paper aims to shed light on the home country determinants and their relationship with investments into the Republic of Ireland. Using panel data analysis for 28 different countries around the world from the years 2012 to 2019, this paper aims to find relationships between different home country related variables and FDI flows into the Republic of Ireland. We find evidence that FDI is positively associated with the market size of the home country, the corporate tax rate difference between the home and the host country and sharing an official language. On the other hand, population and distance were found to be negatively associated with FDI. Based on the results of our analysis, a discussion of the home country determinants and their impact on FDI into Ireland is presented.