Destroyed Railroad Wagon in Mero Laburcz Military; World War I

Bernhard Bardach World War I Album I

Social organization of household finance: Understanding artful financial systems in the home

In this paper we discuss results of a field study focused on understanding the ways money and financial issues are handled within family settings. Families develop ‘systems’ or methods through which they coordinate and manage their everyday financial activities. Through an analysis of our fieldwork data collected from fifteen families, we provide several examples of such systems, highlighting their qualities and illustrating how such systems come to support the handling of financial activities in the home. Our results show that these systems are developed with a careful consideration of familial values, relationships and routines; and incorporate the use of physical and digital tools. Consequently, we suggest that design should consider the use and non-use of technology when supporting household financial management, taking into account the richness of families’ existing organically formed practices surrounding financial systems. Finally, our findings point to the fact that financial management in the domestic setting is socially organized and is closely connected to supporting everyday household activities.

Studies on Binary Time Series Models with Applications to Empirical Macroeconomics and Finance

This thesis studies binary time series models and their applications in empirical macroeconomics and finance. In addition to previously suggested models, new dynamic extensions are proposed to the static probit model commonly used in the previous literature. In particular, we are interested in probit models with an autoregressive model structure. In Chapter 2, the main objective is to compare the predictive performance of the static and dynamic probit models in forecasting the U.S. and German business cycle recession periods. Financial variables, such as interest rates and stock market returns, are used as predictive variables. The empirical results suggest that the recession periods are predictable and dynamic probit models, especially models with the autoregressive structure, outperform the static model. Chapter 3 proposes a Lagrange Multiplier (LM) test for the usefulness of the autoregressive structure of the probit model. The finite sample properties of the LM test are considered with simulation experiments. Results indicate that the two alternative LM test statistics have reasonable size and power in large samples. In small samples, a parametric bootstrap method is suggested to obtain approximately correct size. In Chapter 4, the predictive power of dynamic probit models in predicting the direction of stock market returns are examined. The novel idea is to use recession forecast (see Chapter 2) as a predictor of the stock return sign. The evidence suggests that the signs of the U.S. excess stock returns over the risk-free return are predictable both in and out of sample. The new "error correction" probit model yields the best forecasts and it also outperforms other predictive models, such as ARMAX models, in terms of statistical and economic goodness-of-fit measures. Chapter 5 generalizes the analysis of univariate models considered in Chapters 2 4 to the case of a bivariate model. A new bivariate autoregressive probit model is applied to predict the current state of the U.S. business cycle and growth rate cycle periods. Evidence of predictability of both cycle indicators is obtained and the bivariate model is found to outperform the univariate models in terms of predictive power.

Panama Railroad Station, Balboa, Canal Zone - Old Timers arriving Jan. 18, 1928

Leonard Carpenter Panama Canal Collection. Photographs: Views of Panama and the Canal. [Box 1] from the Special Collections & Area Studies Department, George A. Smathers Libraries, University of Florida.

International Climate Finance and its Influence on Fairness and Policy

27 p.

Experiment on Qinghai-Tibet railroad subgrade temperature monitoring based on FBG sensors

Qinghai-Tibet Railway is the longest and highest plateau railway in the world. A long term monitoring system of the stability of the subgrade in the permafrost regions should be put forward immediately to prevent damage to the railway. As it's very difficult to set up the long-distance automatic monitoring system which contains a lot of measure points along the 550 kilometers railway in the permafrost area, we present a subgrade temperature monitor system based on fiber Bragg grating (FBG). In this paper the principles of the FBG was presented, and the feasibility of the FBG sensors in the permafrost area of Qinghai-Tibet plateau was analysized. We embedded fifteen FBG temperature sensors and thermal resistance temperature sensors. A contrast experiment is made while the two kinds of sensors are arranged in the same position. The result of the experiment shows that the accuracy of the FBG temperature sensors is less than 0.1 degrees C. and the FBG sensors can do well in the measurement of pattern which the temperature varies with the depth of the permafrost soil. The result also shows the stability of the FBG sensors in the bad environmental condition of Qinghai-Tibet plateau, which proves the feasibility of the application of FBG sensors and our monitoring system on the Qinghai-Tibet railway.