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.

In recent years, investors have become more concerned about where they invest their capital and how to spread the risk among different asset types. The interest in commercial real estates has increased as this market is seen as less volatile than the stock market. Previous research for other economies has found that the commercial real estate market and the stock market do not cointegrate. Therefore it is possible to invest in both asset classes to create diversified portfolios. This thesis examines if such cointegration relationship exist on the Swedish market. Furthermore, the thesis examines the correlation and the lead-lag relationship between the two asset classes. The observed data is quarterly between the years 1994-2013 and the indices used are OMX Stockholm, sold multi-dwelling and commercial buildings, and sold manufacturers industries. To examine if there exist any cointegration between the indices the Engle-Granger 2-step method is used and the lead-lag relationship is tested by using the Granger Causality test. The results from the different tests do not show any short- or long-term relationship between the Swedish stock market and the Swedish commercial real estate market, neither do the assets show any lead-lag relationship. This means that the portfolio risk decreases and it is therefore possible for investors to diversify their portfolios with both short- and long-term time horizons.

本篇論文使用Correlation of Coefficient 與 Johansen cointegration test來探討股票市場與匯率市場之間的連動性。實證結果顯示股票市場與匯率市場之間有高度的相關性，特別是在西元2000年之後，全球呈現出集體的連動性。而此兩變數之間的關係亦可在不同的地區或是不同的工業化程度國家下看見不同的結果，歐體以及諸多新興市場等區域內皆呈現出股市與匯市相關係數的一致性。然而，當此研究以Johansen cointegration test來分析時，無法在此兩研究變數間發現顯著的長期關係。 / This study utilized Correlation of Coefficient as well as Johansen cointegration test to investigate the relationship between stock prices and exchange markets. The empirical results show that the two markets of study are highly correlated, especially after the year of 2000. Since then, the stock prices and exchange rates worldwide have presented one common trend, either negative correlation or positive. Different region, such as European Union or East Asian countries exclude Japan, and different level of industrialization lead to diverse relationship between exchange rates and stock prices. Put this relationship in a long-term scope, however, no distinct trend can be discerned by using Johansen cointegration test.

This volume contains five essays in the field of time series econometrics. All five discuss properties of fractionally integrated processes and models. The first essay, entitled Do Long-Memory Models have Long Memory?, demonstrates that fractional integration can enhance the memory of ARMA processes enormously. This is however not true for all combinations of diffe-rencing, autoregressive and moving average parameters. The second essay, with the title On the Effects of Imposing or Ignoring Long-Memory when Forecasting, investigates how the choice between mo-delling stationary time series as ARMA or ARFIMA processes affect the accu-racy of forecasts. The results suggest that ignoring long-memory is worse than imposing it and that the maximum likelihood estimator for the ARFIMA model is to prefer. The third essay, Power and Bias of Likelihood Based Inference in the Cointegration Model under Fractional Cointegration, investigates the performance of the usual cointegration approach when the processes are fractionally cointegrated. Under these circumstances, it is shown that the maximum likelihood estimates of the long-run relationship are severely biased. The fourth and fifth essay, entitled respectively Bootstrap Testing for Fractional Integration and Robust Testing for Fractional Integration using the Bootstrap, propose and investigate the performance of some bootstrap testing procedures for fractional integration. The results suggest that the empirical size of a bootstrap test is (almost) always close to the nominal, and that a well-designed bootstrap test is quite robust to deviations from standard assumptions. / Diss. Stockholm : Handelshögsk. [7] s., s. x-xiv, s. 1-26: sammanfattning, s. 27-111, [4] s.: 5 uppsatser

The purpose of the paper is to explore the relationship between inflation and unemployment in Germany during the period from 1970 to 2012. Through the methods of cointegration, dynamic OLS and an error correction model, this paper highlights that there is no short run negative relationship between inflation and unemployment, and consequently the short run Phillips curve is an unsuitable instrument for making political decisions. Furthermore, there is a long run relationship between inflation and unemployment, which can be explained with asymmetric nominal wage rigidities and resulting frictional growth. Resulting policy implications reflect the advantage of a permanent higher inflation target for Germany. Since the beginning of the European Monetary Union, Germany has been on average 0.5% under the permanent inflation target of the central bank. Therefore, by using fiscal policy, Germany can reduce permanent unemployment without missing the inflation target of the central bank. Finally, despite of variety of intensive changes in the macroeconomic situation and particularly through the establishment of the European Monetary Union, the CUSUM and CUSUMsq test reveal that the estimate holds validity over the entire observation period and has not changed since the beginning of the European Monetary Union.

Thesis (Ph. D.)--University of California, San Diego, 2000. / Vita. Includes bibliographical references.

Thesis (Ph. D.)--University of California, San Diego, 1997. / Vita. Includes bibliographical references.

Diss.--Universität Basel, 2005. / Description based on print version record. Includes bibliographical references.

Thesis (Ph. D.)--University of California, San Diego, 2006. / Title from first page of PDF file (viewed September 20, 2006). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references.

The paper describes an attempt to gain insight into the relationship between cash and futures markets for US lean hogs and EU live pigs, and the opportunity of arbitrage hedging. In doing so, the authors use newer methods of threshold cointegration analysis for time series from 1999 until 2008. Besides the existence of a long-run equilibrium, asymmetric price adjustments can be demonstrated. This is especially the case for the EU live pigs, where price variations of the basis are higher and exhibit lower standard deviation. The results also perfectly show that cash prices follow the futures market more than the other way round. Furthermore, a grid search has revealed that the residual-based threshold in either market is near zero and therefore coherent with economic interpretation. Thus, at least theoretically, arbitrageurs in those markets are able to exploit the price differences between the two markets and reap no-risk monetary benefit. Hence, the results are in line with the statement that "speculating the basis" generates a better return. (authors' abstract)