The dissertation analyzes the impact of Foreign Direct Investment (FDI) on Economic Growth by extension and economic development of the regions of the Czech Republic (CZ) in 1998 -- 2011. Statistical data empirically study determined motivation of investors to locate in economically strong regions. Following the analysis of statistical data, available resources and a field survey, whose output includes three case studies of specific Foreign Investments in the Czech Republic, the analysis examines whether the arrival of a significant foreign direct investor in the region significantly influenced selected characteristics of economic performance, or other selected areas in region (social, environmental, transport etc.). Moreover, in the context of econometric analysis to test the tightness of the relationship between Foreign Direct Investment and Economic Growth using Pearson's coefficient and characteristics of variability. The causal effect of Foreign Direct Investment on Economic Growth (and vice versa) is analyzed using Granger causality test. The conclusion gives an assessment of the significance of Foreign Direct Investment in the regions of the Czech Republic together with the identification of significant effects brought by investments.

Thesis (M.Com. (Economics)) -- University of Limpopo, 2020 / The remarkable increase in FDI flows to developing countries over the last decade has focused attention on whether this source of financing enhances overall development and growth in the economy. To attain foreign direct investment and sustainable economic growth of a country, balanced budget is not only important but necessary. The aim of the study was to examine the nexus between foreign direct investment (FDI) inflows and budget deficit in a panel of five Southern African Development Community (SADC) countries (Malawi, South Africa, Tanzania, Namibia, and Zambia). The study employed the Panel Auto Regressive Distributed Lag (PARDL) model in examining the relationship between budget deficit and FDI. The panel unit root tests results showed different orders of integration (at levels and first-order) giving way to the use of PARDL. Co-integration test results confirmed a long-run relationship in the budget deficit FDI series. In the long run, there is a significant negative relationship between budget deficit and FDI. The speed of adjustment is 36%, implying that the system would converge faster to equilibrium. Furthermore, Granger causality test results indicated a bi-directional causal link on the interest rate – inflation and interest rate – FDI models. However, there is a unidirectional causality running from budget deficit to FDI; interest rate to the budget deficit and FDI to inflation. It is recommended that government should attract more foreign direct investment so as to minimise budget deficit and this could speed up the development of SADC countries. Key Terms: Foreign direct investment, budget deficit, Autoregressive-Distributed Lag, panel data, Granger causality.

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Juraj Bodík Abstract This thesis is dealing with the following problem: Let us have two stationary time series with heavy- tailed marginal distributions. We want to detect whether they have a causal relation, i.e. if a change in one of them causes a change in the other. The question of distinguishing between causality and correlation is essential in many different science fields. Usual methods for causality detection are not well suited if the causal mechanisms only manifest themselves in extremes. In this thesis, we propose a new method that can help us in such a nontraditional case distinguish between correlation and causality. We define the so-called causal tail coefficient for time series, which, under some assumptions, correctly detects the asymmetrical causal relations between different time series. We will rigorously prove this claim, and we also propose a method on how to statistically estimate the causal tail coefficient from a finite number of data. The advantage is that this method works even if nonlinear relations and common ancestors are present. Moreover, we will mention how our method can help detect a time delay between the two time series. We will show how our method performs on some simulations. Finally, we will show on a real dataset how this method works, discussing a cause of...

Dividend policy is widely researched in financial management, but determining whether it affects the market price per share is difficult. There has been much published on the subject, which presented theories such as the Modigliani, Miller, Gordon, Lintner, Walter and Richardson propositions and the relevance and irrelevance theories. However, little research has been done on the impact of dividend policy on shareholders’ wealth while considering the short- and long-run effects. The Vector Error Correction Model (VECM) was used to describe the short-run and long-run dynamics or the adjustment of the cointegrated variables towards their equilibrium values in South Africa. This study attempts to explain the effect of dividend policy on the market price per share. A sample of 46 companies listed on the Johannesburg Securities Exchange (JSE) was selected for the period 1995-2010. Three variables were used, namely the market price per share, the dividend per share and the earnings per share. The market price per share was used as a proxy in measuring shareholders’ wealth and the dividend per share was used as a proxy in measuring the dividend policy. Fixed and random effects models were applied to panel data to determine the relation between dividend policy and market price per share. The fixed effects method was used to control the stable characteristics of the companies over a fixed period. The random effects model was applied when the companies’ characteristics differed. Results for both models indicated that dividend yield is positively related to market price per share, while earnings per share do not have a significant impact on the market price per share. To test the strength of the long-run relationship, the VECM was applied. The coefficient for dividend per share in the co-integrating equation was positive, while the coefficient for earnings per share was negative. This confirms previous research findings. The results suggest that there is a long-run relationship between dividend per share and market price per share. The Granger causality test indicates there is bi-directional Granger causality between market price per share and dividend per share in South Africa. Therefore dividend policy does have a significant long-run impact on the share price and therefore provides a signal about the company’s financial success. / Dissertation (MCom)--University of Pretoria, 2012. / Financial Management / Unrestricted

京都大学 / 0048 / 新制・課程博士 / 博士(医学) / 甲第18506号 / 医博第3926号 / 新制||医||1005(附属図書館) / 31392 / 京都大学大学院医学研究科医学専攻 / (主査)教授 河野 憲二, 教授 髙橋 良輔, 教授 福山 秀直 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

Thesis (M.Sc. (Agricultural Economics)) -- University of Limpopo, 2022 / Agricultural production measures the performance and efficiency of a country’s agricultural sector. The state of agricultural production can be assessed through the value of agricultural production, which is a product of agricultural gross production and output prices in monetary terms. The study examines the relationship between the value of agricultural production, government spending on agriculture, and other selected variables. Annual data for the value of agricultural production, government expenditure in agriculture, consumer price index, average annual rainfall, food import value, and population from 1983 to 2019 were collected from different sources and were used in the analysis for this study. The Johansen cointegration test was used to determine the existence of a long-run relationship between the value of agricultural production and selected variables by using both the trace and eigenvalue tests. The results indicated that there is a long run relationship among the variables. The study further used the Granger causality test to check the causality between the value of agricultural production and government expenditure in agriculture. The results show that there is no causal effect between the two variables. Lastly, the study used a Vector autoregressive (VAR) model to determine the relationship between the value of agricultural production and selected variables. The results of the VAR model indicated that government expenditure on agriculture, average annual rainfall, food import value, and population positively affect the value of agricultural production. The study also found that the consumer price index negatively affects the value of agricultural production. The study recommends that the government increase its spending on the agricultural sector, which could be in the form of research investment in technologies such as climate-smart agricultural technologies. Additionally, the study recommends that policymakers should review the monetary policy of South Africa to ensure price stability and prevent inflation. Lastly, the study recommends that the South African government should discourage imports and encourage South African agricultural producers to produce more major imported food products.

The study investigates the linkages between government policies and the real estate sector via a case study that was carried out on the Japanese market. The applicability of the results were then discussed in terms of whether similar trends could be seen in other economies facing similar demographic and economic issues as Japan. While the real estate sector linkages with the overall economy are relatively well studied topic, there are less studies regarding the links between government policies and the real estate market. The studies in the field furthermore in general conclude that the results are country and location dependent, thus illustrating there to be a research gap. Given that real estate sector is linked with the overall performance of the economy, and fluctuations within the sector can magnify ups and downs of the overall economy, it is of importance to investigate the topic in order to, for example, illustrate the effect that policy changes will have on the real estate sector and thus potentially also on the overall market. The approach of the study was to carry out quantitative analysis through the use of econometric analysis methods such as cointegration and Granger causality. The robustness of the econometric analysis results were then further discussed through the use of qualitative analysis tool of expert interviews. The applicability of the econometric results to other economies was analyzed with simple comparison of key variables. The results of the study indicate that government policies have very little effect on the real estate sector. The econometric analysis suggests that neither monetary nor fiscal policy had notable effect on the real estate sector, especially price development. On the other hand, interest rates were seen as a most notable government policy tool to have an effect on the real estate sector in the expert interviews. As a conclusion, it was argued that the low level of cointegrations and lack of causalities could be due to government policies having an indirect effect on the real estate market via altering the demand and supply for real estate rather than leading to changes within the sector directly. For the comparison, some of the Nordic countries and Germany were noted to be facing similar issues as Japan in terms of ageing population, urbanization trend, notable government debt levels, and low interest rates. It was however noted, that the econometric analysis results could not be mirrored to these markets directly due to the rather straightforward comparison, but rather the results could act as a guideline. / Den här studien utreder kopplingarna mellan regeringspolitiken och fastighetssektorn genom en fallstudie som utfördes på den japanska marknaden. Tillämpligheten av studiens resultat diskuterades sedan kring huruvida liknande trender kan utläsas i andra ekonomier som står inför liknande demografiska och ekonomiska problem som Japan gör.  Hur fastighetssektorn är kopplad till den generella ekonomin är ett relativt välstuderat ämne, de finns däremot färre studier som avhandlar kopplingar mellan regeringspolitik och fastighetsmarknadens utveckling. Studierna inom ämnet sammanfattar generellt att studiens resultat är beroende av landet och den specifika platsen, vilket visar att det finns en lucka i forskningen. Med tanke på att fastighetsmarknaden är kopplad till den generella ekonomins utveckling, samt att fluktuationer inom sektorn kan förstora upp- och nedgångar i den övergripande ekonomin, är det väsentligt att undersöka ämnet för att, exempelvis, illustrera den effekt politiska ändringar har på fastighetssektorn och därmed potentiellt den övergripande marknaden.  Studiens tillvägagångsätt var att genomföra en kvantitativ analys genom användning av ekonometriska analysverktyg, såsom samverkan och Granger kausalitet. De ekonometriska analysresultatens robusthet diskuterades därefter ytterligare genom kvalitativ analys i form av intervjuer med experter inom ämnet. De ekonometriska resultatens, till andra ekonomiers, användbarhet analyserades med en enkel jämförelse av nyckelvariabler.  Resultatet av studien indikerar att regeringspolitik har en mycket liten effekt på fastighetssektorn. Den ekonometriska analysen tyder vidare på att varken penning- eller finanspolitik har en märkbar effekt på fastighetssektorn, i synnerhet på prisutvecklingen. Motsatt till detta framgick det i intervjuerna med experter inom ämnet, att räntorna är det verktyg som används inom regeringspolitiken som har störst effekt på fastighetssektorn. Som slutsats hävdades det att den låga graden samverkan och bristen på kausalitet kan bero på att regeringspolitik har en indirekt effekt på fastighetssektorn då utbudet och efterfrågan ändras snarare än att det direkt leder till ändringar inom sektorn. Vad gäller tillämpningen av de ekonometriska resultaten noterades det att några av de nordiska länderna samt Tyskland kommer att möta liknande problem som Japan, gällande åldrande befolkning, urbaniseringsutveckling och låga räntor. Det noterades dock att de ekonometriska analysresultaten inte direkt kunde spegla sig i dessa marknader då en relativ enkel jämförelsemetod användes, men att resultaten kan agera som en riktlinje.

This study will be investigating the relationship between short-term and long-term interest rates with the OMX30 stock return expressed in percentage, as well as the effect that the interest rates have on the stock return. The data used in this study has been collected from the dataprogram Datastream with monthly observations from January 2003 until December 2022 resulting in 240 different variables within all three factors over a period of 20 years. While performing OLS estimation, the result estimated by using R-studio shows a negative correlation between the interest rates and the percentage return of OMX30. Furthermore, the Granger causality test shows that the short-term interest rate does have an impact on the market whilst the long-term interest rate does not have any direct effect on the stock market in Sweden.

Thesis (M.Sc. Agriculture (Agricultural Economics)) -- University of Limpopo, 2022 / Beef and chicken meat play a very crucial role in providing food to South African consumers. However, the rise of food prices in South Africa is viewed to curtail progress and drives consumers into debt and forgone opportunity to access food. Hence, it is of importance to understand the consumer price index (CPI) of meat and the disaggregate components of beef and chicken meat producer price indexes (PPI) as they give a clear insight into how individual commodities contribute to the general and food price inflation. The study aimed to comparatively analyse the relationship between PPI beef and CPI meat as well as PPI chicken meat and CPI meat in South Africa from 1991 to 2018. The objectives of the study were to compare the indexes’ variability, correlation, and causality between the different PPI and CPI components. The objectives were analysed using the Coefficient of variation (CV), the Pearson coefficient correlation, the Granger causality test, and the Vector Error Correction model. The CV findings highlight that PPI beef had high variability (65%) compared to CPI meat (56.7%), whereas PPI chicken meat had low variability (49.2%) compared to CPI meat(56.7%). There was evidence of a positive correlation (0.99) between PPI beef and CPI meat as well as PPI chicken meat and CPI meat using Pearson coefficient correlation. In addition, a long-run relationship was found between PPI beef and CPI meat as well as between PPI chicken meat and CPI meat by using the VEC model. Granger causality results indicated that there was a unidirectional relationship from PPI chicken meat to CPI meat, and independent relationships were found from PPI beef to CPI meat, CPI meat to PPI beef as well as CPI meat to PPI chicken meat. Based on the findings, the study recommends that policymakers, through evaluation of monetary policies, should continue maintaining a specific inflation target range as that will assist in stabilising meat prices in the economy. At the same time, protect meat producers against input price inflation using instruments such as input subsidies, grants, and the provision of modern technologies. / National Research Foundation (NRF)