No description available.

Housing bubbles could have a great impact on the economy of a country, especially for a country as large as China. Therefore, it is necessary to evaluate the housing bubble situation of a region. Based on the classification of cities, this research has selected Yangzhou as the main research sample to predict the overall situation of housing bubble in third-level cities in China. The paper integrates the relevant theories and methods of the housing bubble research mentioned in the literature, and seeks out a set of suitable real estate bubble research methods: using ADF test, EG cointegration analysis to see whether the indicators are suitable as variables in the Granger causality test and regression analysis, and then perform regression analysis on the appropriate variables and housing prices to judge the real estate bubble. Also, the result of Yangzhou is applied to compare with that of Beijing and Shanghai so as to get the difference of real estate markets between first- and third-level cities. / Bostadsbubblor kan ge allvarlig inverkan på ett lands ekonomi, särskilt för ett så stort land som Kina. Därför är det nödvändigt att utvärdera om eventuella bostadsbubblor förekommer i olika regioner. I detta arbete analyseras förekomsten av en bostadsbubbla i en av Kinas städer i den tredje storleksklassen enligt det kinesiska klassificeringssystemet. Studieobjektet som valts är Yangzhou. I uppsatsen diskuteras de relevanta teorier och metoder som förekommer i litteraturen för analys av bostadsbubblor och ett antal metoder tillämpas. ADF-test och Engel-Grainer-kointegration används för att avgöra vilka av de tillgängliga marknadsindikatorerna som är lämpliga att använda vid test av Granger-kausalitet och i regressionsanalyser. Regressioner med de utvalda variablerna görs sedan mot bostadspriser för att erhålla mått på förekomsten av en bostadsbubbla. De empiriska resultaten från studien jämförs också med resultat för Beijing and Shanghai för att påvisa skillnader mellan marknaderna i städer av första respektive tredje storleksklassen.

第一章 台灣與美國股市價量關係的分量迴歸分析 摘要 本文利用分量迴歸來觀察台灣和美國股市報酬率和成交量的價量關係。實證結果發現兩地股市的價量關係截然不同。台灣股市的報酬率與成交量之間具有正向關係，呈現「價量齊揚」和「價跌量縮」的現象，而前者效果通常較顯著；但報酬率接近最大漲幅限制時，報酬率與成交量之間並無顯著關係，報酬率接近最大跌幅限制時，「價跌量縮」的現象甚至更強。相對於台灣，美國股市的報酬率與成交量則出現「價量齊揚」與「價量背離」互相對稱的 “V” 字關係。就實證方法而言，傳統以 OLS 方法估計的迴歸模型並無法得到上述的實證結果。進一步的分析顯示，融券成數的高低以及平盤以下不得放空等規定都是造成台灣股市出現「價跌量縮」的可能原因。 第二章 股市價量關係的分量迴歸分析 (二) 摘要 本章利用分量迴歸觀察包括台灣在內的亞洲新興工業國家與成熟股市的價量關係。實證結果顯示，亞洲新興工業國家和日本股市「價量齊揚」的效果較強，其中香港、南韓和新加坡呈現較弱的「價量背離」現象，因此價量之間有不對稱的 “V” 字關係；而日本股市則呈現「價跌量縮」，與第一章分析的台灣股市價量關係相似。在成熟股市的價量關係中，英國金融時報指數、美國道瓊工業指數和德國股價指數皆呈現對稱的 “V” 字關係，與美國US指數的價量關係相似。亞洲地區的國家在1997下半年到1998上半年普遍經歷了一場金融風暴，本文進一步的分析發現在這場風暴期間，亞洲地區除了台灣以外，日本、香港、南韓與新加坡都出現較強的「價量齊揚」與「價量背離」，這種現象可能肇因於投資人認為風暴期間的股價報酬率風險較高，遂使得股價報酬率對成交量的反應較為敏銳。相對而言，歐美地區的國家，受到亞洲金融風暴的影響較小，所以整體的價量關係在亞洲金融風暴期間並無重大改變。本章的結果都是透過分量迴歸所獲得。 第三章 股市價量因果關係的分量迴歸分析 摘要 本文依據分量迴歸設計 Granger 因果關係的新檢驗方法，並依此方法來檢驗幾個股市價量之間的因果關係。本文分析的股市包括日本、英國與美國等世界前三大股市，以及合稱亞洲四小龍的台灣、香港、南韓與新加坡等新興工業國家或地區的股市。實證結果顯示：除了台灣股市以外，其他的股市皆呈現 “V” 字的跨期價量關係。其中英國、美國、香港和新加坡股市的跨期價量關係大體呈現正向「價量齊揚」與負向「價量背離」互相對稱的 “V” 字關係，而日本和南韓股市則是「價量齊揚」較強的不對稱 “V” 字關係。此一結果表示這些股市的價量之間都存在分配上的 Granger (1969) 因果關係。但若以均數迴歸來衡量跨期價量關係，則所有股市都呈現不顯著的跨期價量關係，也就是傳統文獻上所謂價量之間沒有 Granger 因果關係。本文所提出的 Granger 因果關係之分量迴歸分析，可以觀察到整個條件分配中各分量的因果關係，為分配上的 Granger 因果關係提供一個較完整的檢驗方法。 / We examine the relationship between the stock return and trading volume in the Taiwan and U.S. Stock Exchanges using quantile regression. The empirical results show that the return-volume relations in these two exchanges are quite different. For Taiwan data, there are significant positive return-volume relations across quantiles, showing that a large positive return is usually accompanied with a large trading volume and a large negative return with a small trading volume, yet the effect of former is stronger. However, such relations change when returns approach the price limits. We also find that for U.S. data, return-volume relations exhibit symmetric V-shapes across quantiles, showing that a large return (in either sign) is usually accompanied with a large trading volume. On the other hand, linear regressions estimated by the ordinary least square method are unable to reveal such patterns. Further investigation shows that various restrictions on short sales in the Taiwan Stock Exchange may explain the difference between the return-volume relations in Taiwan and U.S. data.

In this study, linear and nonlinear Granger causality tests are used to examine the dynamics, including return to return and volume to volume relationships, between warrants and their underlying stocks in Taiwan Stock Exchange (TSEC). Results of previous studies are mixed and they only focus on linear relationship between the two markets. Here we take nonlinear relationship into consideration to assist in investigating what the direction of information flow is. We use intraday five-minute high frequency data and the result tells that, overall, for both return to return and volume to volume relations, there is bidirectional but asymmetry linear causality and weak unidirectional nonlinear causality from stock to warrant market between these two markets. Combining the linear and nonlinear results we conclude that the direction of information flow is mainly from stock market to warrant market.

This study aims to determine the main drivers of financial market development, with a specific interest in the relationship between the stock and bank credit markets, as proxies of financial market development, and the role of institutional quality, in ten African countries for the period of 2009 to 2017. A number of econometric techniques such as the General Methods of Moments (GMM) model for dynamic panel data, autoregressive distribution lag (ARDL) bound testing approach to cointegration, vector error correction model (VECM), and granger causality tests were applied in the study. We further developed a composite index for both financial market development and institutional quality using Principal Components Analysis (PCA). The results demonstrate that institutional quality, as well as infrastructure development, economic growth, and inflation are the main determinants of financial market development in our sample of ten African countries. Findings from the ARDL bound testing approach confirm the existence of a long-run association between institutional quality and financial market development. Although financial market development has no effect on economic growth, institutional quality was found to have a positive and highly significant effect on economic growth. Furthermore, employing the Granger causality test, we found uni-directional granger causality between financial market development and institutional quality, implying that financial market development is a significant causal factor for institutional quality. In consideration of these findings, policy formulation by governments should be designed towards enhancing financial and institutional quality development, and this can be possibly achieved by effective enforcement of law to encourage compliance, while simultaneously eliminating corruption and other institutional hindrances to development / Lolu cwaningo luhlose ukuveza izinhlaka ezingabaphembeleli abasemqoka ekuthuthukisweni kwezimakethe zezimali, kugxilwe kakhulu kubudlelwano obuphakathi kwesitoko kanye nezimakethe zamabhangi ahlinzekana ngezikweletu, njengabancedisi abathuthukisa izimakethe zezimali, kanye nendima emayelana nezinga leziko, emazweni ase-Afrika ayishumi esikhathini esiphakathi kuka 2009 ukufikela ku 2017. Inani lezindlela zokulinganisa izinga lomnotho ezinjenge-General Methods of Moments (GMM) model yedatha yephaneli eguquguqukayo, i-autoregressive distribution lag (ARDL) bound testing approach to cointegration, i-vector error correction model (VECM), Kanye negranger causality tests zisetshenzisiwe kucwaningo. Siqhubekele phambili nokwakha inkomba ehlangene yazo zombili izinhlaka; ukuthuthukiswa kwezimakethe zezimali Kanye nezinga leziko ngokusebenzisa uhlelo lwe-Principal Components Analysis (PCA). Imiphumela ikhombisile ukuthi izinga leziko, Kanye nokuthuthukiswa kwengqalasizinda, ukuhluma komnotho, Kanye nezinga lamandla email yizinkomba ezisemqoka zokuthuthukiswa kwezimakethe zezimali kusampuli yethu elula yamazwe ase-Afrika ayishumi. Ulwazi olutholakele ku-ARDL bound testing approach luqinisekisa ubukhona kobudlelwano besikhathi eside obuphakathi kwezinga leziko kanye nokuthuthukiswa kwezimakethe zezimali. Yize ukuthuthukiswa kwemakethe yezimali kungenawo umthelela kwezokuhluma komnotho, izinga leziko lona liye latholakala ukuthi linomthelela omuhle nosemqoka kakhulu ekukhuleni komnotho. Ngaphezu kwalokho, uma sisebenzisa uhlelo lweGranger causality test, sifumene i-uni-directional granger causality phakathi kwemakethe yezimali Kanye nezinga leziko, lokhu kuchaza ukuthi ukuthuthukiswa kwezimakethe zezimali kuyimbangela esemqoka yezinga leziko. Uma kubhekwa lolu lwazi olutholakele, imigomo eyakhwa uhulumeni kufanele yakhiwe ngenhloso yokuqinisa ukuthuthukiswa kwezinga lezimali Kanye nezinga leziko, kanti lokhu kungafinyelelwa ngokuqinisa kahle umthetho ukukhuthaza ukulandelwa komthetho, kanti ngakolunye uhlangothi kuncishiswe izinga lenkohlakalo Kanye nezinye izihibhe eziphazamiso ukuthuthukiswa kweziko. / Maikaelelo a thutopatlisiso ke go swetsa ka ditsamaisi tse dikgolo tsa tlhabololo ya mebaraka ya ditšhelete, ka kgatlhego e rileng mo kamanong magareng ga mebaraka ya setoko le ya sekoloto sa dibanka, jaaka kemedi ya tlhabololo ya mebaraka ya ditšhelete, le seabe sa boleng jwa ditheo, mo dinageng di le lesome tsa Aforika mo pakeng ya 2009 go ya go 2017. Go dirisitswe dithekeniki di le mmalwa tsa ikonometiriki di tshwana le sekao sa General Methods of Moments (GMM) sa data ya phanele e anameng, molebo wa tekeletso e kopanyang ya autoregressive distribution lag (ARDL), sekao sa vector error correction (VECM) le diteko tsa sesusumetsi tsa Granger. Gape re tlhamile tshupane ya dikarolo ya tlhabololo ya mmaraka wa ditšhelete le boleng jwa ditheo re dirisa Tokololo ya Dikarolo tse Dikgolo (Principal Components Analysis (PCA)). Dipholo di bontsha gore boleng jwa ditheo, gammogo le tlhabololo ya mafaratlhatlha, kgolo ya ikonomi le infoleišene ke diswetsi tsa tlhabololo ya mebaraka ya ditšhelete mo sampoleng ya rona ya dinaga di le lesome tsa Aforika. Diphitlhelelo go tswa mo molebong wa teko e kopanyang ya ARDL di tlhomamisa go nna teng ga kamano ya paka e telele magareng ga boleng jwa ditheo le tlhabololo ya mebaraka ya ditšhelete. Le fa tlhabololo ya mebaraka ya ditšhelete e sa ame kgolo ya ikonomi ka gope, boleng jwa ditheo bo fitlhetswe bo na le ditlamorago tse di siameng e bile di le botlhokwa mo kgolong ya ikonomi. Mo godimo ga moo, ka go dirisa teko ya Granger ya sesusumetsi, re fitlhetse go na le sesusumetsi sa ntlha e le nngwe sa Granger magareng ga lhabololo ya mebaraka ya ditšhelete le boleng jwa ditheo, mo go rayang gore tlhabololo ya mebaraka ya ditšhelete ke ntlha e e botlhokwa ya sesusumetsi sa boleng jwa ditheo. Fa go lebelelwa diphitlhelelo tseno, go dirwa ga dipholisi ke dipuso go tshwanetse ga dirwa gore go tokafatse tlhabololo ya boleng jwa ditšhelete le ditheo, mme seno se ka fitlhelelwa ka tiragatso e e bokgoni ya molao go rotloetsa kobamelo mme go ntse go fedisiwa bobodu le dikgoreletsi tse dingwe tsa tlhabololo mo ditheong. / Business Management / M. Com. (Business Management (Finance))

Exponential smoothing algorithms are very attractive for the practical world such as in industry. When considering bivariate exponential smoothing methods, in addition to the properties of univariate methods, additional properties give insight to relationships between the two components of a process, and also to the overall structure of the model. It is important to study these properties, but even with the merits the bivariate exponential smoothing algorithms have, exponential smoothing algorithms are nonstatistical/nonstochastic and to study the properties within exponential smoothing may be worthless. As an alternative approach, the (bivariate) ARIMA and the structural models which are classes of statistical models, are shown to generalize the exponential smoothing algorithms. We study these properties within these classes as they will have implications on exponential smoothing algorithms. Forecast properties are studied using the state space model and the Kalman filter. Comparison of ARIMA and structural model completes the study. / Mathematical Sciences / M. Sc. (Statistics)

In the literature there are mixed results on the link between credit and agricultural output growth. Some authors argue that credit leads to growth in agricultural output. Others view growth as one of the factors that influence credit supply, thus growth leads and credit follows. By and large, studies have not endeavoured to establish the short-run impact of agricultural credit on output. They are generally limited in establishing the long-run relationship between credit and agricultural output and thus present a research gap in this respect. This study contributes to the existing body of literature by focusing on the finance-growth nexus at sectoral level as a departure from extant literature that has focused on the macroeconomic level. Using South African data, the study investigated the causal relationship between the supply of credit and agricultural output as well as whether the two are cointegrated and have a short-run relationship. The study found that bank credit and agricultural output are cointegrated. Using the error correction model (ECM), the results showed that, in the short-run, bank credit has a negative impact on agricultural output, reflecting the uncertainties of institutional credit in South Africa. However, the ECM coefficient shows that the supply of agricultural credit rapidly adjusts to short-term disturbances, indicating that there is no room for tardiness in the agricultural sector. The absence of institutional credit will immediately be replaced by availability of other credit facilities from non-institutional sources. Conventional Granger causality tests show unidirectional causality from (1) bank credit to agricultural output growth, (2) agricultural output to capital formation, (3) agricultural output to labour, (4) capital formation to credit, and (5) capital formation to labour, and a bi-directional causality between credit and labour. Noteworthy and significant for South Africa is that for the agricultural sector, the direction of causality is from finance to growth, in other words supply-leading, whereas at the macroeconomic level, the direction of causality is from economic growth to finance, in other words, demand-leading. Applying a structural equation modelling approach to survey data of smallholder farmers, the positive relationship between bank credit and agricultural output observed from analysis of secondary data was confirmed. / Business Management / DCOM (Business Management)

This study provides evidence of the relationship between bank-granted credit and business cycles in South Africa. The study is conducted in three phases, namely qualitative research (Phase I), quantitative research (Phase II) and econometric analysis (Phase III). A sequential (connected data) mixed methodology (Phase I and II) is used to collect and analyze primary data from market participants. The qualitative research (Phase I) involves structured interviews with influential or well informed people on the subject matter. Phase I of the study is used to understand the key determinants of bank credit in South Africa and to appreciate how each of the credit aggregates behaves during alternate business cycles. Qualitative survey results suggest key determinants of commercial bank credit in South Africa as economic growth, collateral value, bank competition, money supply, deposit liabilities, capital requirements, bank lending rates and inflation. The qualitative results are used to formulate questions of the structured survey questionnaire (Quantitative research- Phase II). The ANOVA and Pearman’s product correlation analysis techniques are used to assess relationship between variables. The quantitative results show that there is direct and positive relationship between bank lending behavior and credit aggregates namely economic growth, collateral value, bank competition and money supply. On the other hand, the results show that there is a negative relationship between credit growth and bank capital and lending rates. Overall, the quantitative findings show that bank lending in South Africa is procyclical. The survey results indicate that the case for demand-following hypothesis is stronger than supply-leading hypothesis in South Africa. The econometric methodology is used to augment results of the survey study. Phase III of the study re-examines econometric relationship between bank lending and business cycles. The study employs cointegration and vector error correction model (VECM) techniques in order to test for existence of long-run relationship between the selected variables. Granger causality test technique is applied to the variables of interest to test for direction of causation between variables. The study uses quarterly data for the period of 1980:Q1 to 2013:Q4. Business cycles are determined and measured by Gross Domestic Product at market prices while bank-granted credit is proxied by credit extension to the private sector. The econometric test results show that there is a significant long-run relationship between economic growth and bank credit extension. The Granger causality test provides evidence of unidirectional causal relationship with direction from economic growth to credit extension for South Africa. The study results indicate that the case for demand-following hypothesis is stronger than supply-leading hypothesis in South Africa. Economic growth spurs credit market development in South Africa. Overall, the results show that there is a stable long-run relationship between macroeconomic business cycles and real credit growth in South Africa. The results show that economic growth significantly causes and stimulates bank credit. The study, therefore, recommends that South Africa needs to give policy priority to promotion and development of the real sector of the economy to propel and accelerate credit extension. Economic growth is considered as the significant policy variable to stimulate credit extension. The findings therefore hold important implications for both theory and policy. / Business Management / D.B.L.

Trade liberalization in Kenya started in the early 1980s with the structural adjustment programmes, and continued under the multilateral framework of the WTO. During the same period, the incidence of poverty and level of inequality also worsened. The government’s focus on trade negotiations has been to ensure that there is policy space for the daily running of the economy even though welfare impacts are also important. Non-state actors have argued that trade liberalization has negatively affected the poor; particularly the farmers, since they cannot compete with the developed countries whose farmers enjoy significant government support through subsidies, making their products much cheaper in the world market. Government officials, on the other hand, contend that trade liberalization is good as it brings in competition and transfer of technology which is good for an economy. It is important to examine how trade liberalization has affected household’s welfare in Kenya, given that this kind of analysis has not been conducted in Kenya. This study is unique because it does not assume the existence of a trade liberalization– poverty relationship, unlike most studies. It uses a multi-method approach to first test the hypothesis that there is no statistically significant relationship between trade liberalization and poverty, it further tests for multiplier effects of trade liberalization on poverty determinants. Trade Liberalization and poverty is found to have a stochastic relationship, furthermore investments and capital stock were found to significantly affect poverty determinants in the stochastic model. Due to unavailability of household welfare measure data in time series, a CGE model was used to establish the dynamics of trade liberalization on poverty at a point in time using the 2003 Social Accounting Matrix Data for Kenya. Overall, trade liberalization accompanied by FDI had the greatest impact on household welfare. Trade liberalization had a positive impact on household welfare since household incomes and consumption increased. Micro simulations results, based on changes in consumption, also showed that poverty incidence reduced for all households, even though the urban households experienced higher decreases. The study found that there was little difference in protecting sensitive products and not protecting them; secondly, trade liberalization accompanied by foreign direct investment had greater impact on improving the household welfare. Consumption and incomes increased, resulting in overall poverty reduction. The welfare of urban households was much higher than rural households in terms of income and consumption increases. However, income inequality was much higher in urban than rural areas. / Economics / D. Litt. et Phil. (Economics)

本論述為找出國際化與績效的互動關係。首先，討論銀行國際化誘因，接著建立一國際化指標衡量台灣銀行業國際化程度，再檢驗兩者的關係。 採取1998年到2007年底台灣銀行業各年銀行資料，共計樣本數達486筆。由於資料為縱橫資料，故一般迴歸方式，加入固定效果與隨機效果以檢視不同的銀行特點是否有影響結果。另外檢驗國際化與績效和其他國際化誘因之間是否有互動的因果關係。 將國際化指標定義為海外資產比、海外營收比及海外費用比三者的一般加權指標。國際化誘因則採取：規模、績效、依循客戶、營收市占率、國內外利差、模仿跟風、市場開放與否等八項。結果發現，規模、依循客戶、國外利差等因素都顯著正向影響國際化程度，其中規模及依循客戶又與國際化程度有顯著的因果關係，故可推論國內銀行業國際化的誘因確實有擴大規模及依循客戶的考量。 以實證結果看來，國際化與績效確實會互相影響。另外，考量個別銀行的特性後，台灣銀行業符合固定效果模型。結果顯示，影響銀行績效的因素在不同銀行間沒有很大的差異，然而各銀行所屬的固定特性不同，確實會深刻影響銀行國際化程度的差異，亦即個別銀行的固定特性是影響國際化的重要因素。可見，銀行利用國際化策略而提升銀行績效的做法是有其前提所在，也就是本身條件要好。 銀行國際化、績效、規模等因素就像是一個迴圈，彼此影響。也可以說銀行要提升績效的方式有很多，國際化、併購、擴大市場都是策略之一，只是目前在國內銀行業市場有限的關係，造成國際化策略的自然形成，銀行國際化是一種過程、是一種手段，並不一定與績效有因果關係，只是現在剛好走到這裡。 / This paper examines the relationships between bank performance and DOI(degree of internationalization). We start with explore the incentives for banks to internationalize themselves. Then we structure an index to measure the degree of internationalization and finally examine the relationships between various variables and performance. This study uses unbalanced panel data of the Taiwan bank industry from 1998 to 2007. Besides the often-used regression method, this paper also tests both fixed effect and random effect models with panel data, and examines Granger causality between bank internationalization, performance and incentives of internationalization. We find that variables such as scale, customers-following and foreign interest rate spread positively affect bank internationalization; moreover scale and customers-following factor Granger cause bank internationalization. So we can conclude that utilizing-economies-of-scale and following-customers are two incentives justifying the internationalization strategy of Taiwan’s banks.