The cost structure of U.S. railroad industry, 1980-81

The proposed Coal Rate Guidelines published by the Interstate Commerce Commission imply that the railroad industry can raise rates on the so called captive coal to achieve the goal of revenue adequacy. Revenue adequacy is defined as a level of earnings sufficient to enable a carrier to meet all of its expenses, retire a reasonable amount of debt, cover plant depreciation and obsolescence, and earn a return on investment adequate to attract new capital. If the proposed Coal Rate Guidelines are implemented on coal traffic, it is expected that similar guidelines will be applied to other so called captive commodities, such as grains, fertilizers, chemicals, and agricultural products. The proposed Guidelines emphasize the inelastic demand for railroad transportation of captive coal, but ignore the cost side and the structures of the railroad industry as a crucial part in achieving railroad revenue adequacy;To estimate the potential in achieving the goal of revenue adequacy of the railroad industry from a cost saving point of view, two flexible functional forms, the translog and generalized Leontief models were used to estimate cost behavior under different scenarios. The results indicate that: (1) the railroad industry has substantial returns to traffic density and to average length of haul; (2) the railroad industry has small returns to firm size; (3) the net effects of returns to density, length of haul, and firm size are large and positive; (4) capital and labor are highly substitutable while labor and fuel, and capital and fuel are less substitutable; (5) labor costs are the major component of total costs; (6) all input price elasticities of demand are less than unity; (7) the railroad industry had excess capacity in 1980-81; (8) a cost saving policy can, in part, achieve the goal of revenue adequacy for the railroad industry in 1980-81;This study is based on 1980-81 Class I railroad data, hence the interpretation of the results is limited to the cost structure of these years. As the railroad industry has experienced rapid technological change, further research may be needed when new data become available. Moreover, the model specification can be further improved if less aggregate data are available

Forecasting the Consumption for Electricity in Taiwan

This paper use linear regression and non-linear artificial neural network (ANN) model to analyze how the four economic factors: national income (NI), population (POP), gross of domestic production (GDP), and consumer price index (CPI), affect Taiwan’s electricity consumption, furthermore, develop an economic forecasting model. Both models agree with that POP and NI are of the most influence on electricity consumption, whereas GDP of the least. Then, we compare the out-of-sample forecasting capabilities of the two models. The comparing result indicates that the linear model is obviously of higher bias value than that of ANN model, and of weaker ability of forecasting capability on peaks or bottoms. This probably results from: 1) linear regression model is built on the logarithm function of electricity consumption, and ANN is built on the original data; 2) ANN model is capable of catching sophisticated non-linear integrating effects. Consequently, ANN model is the more appropriate between the two to be applied to building an economic forecasting model of Taiwan’s electricity consumption

Estimating the Capital Structure of High Tech and Traditional Corporations\u27 Capital Structure: Artificial Neural Networks vs. Multiple Linear Regressions

This study adopted multiple linear regression models and artificial neural networks (ANNs) to analyze the important determinants of capital structures of the high tech and traditional corporations in Taiwan, respectively. The ten independent variables (determinants) employed herein included seven corporation feature variables and three external macro-economic variables. The following conclusions were reached: 1) From the root MSE, the ANN model achieved a better fit than the regression model. 2) The capital structure of high tech corporations does not differ significantly from that of traditional corporations, but differences do exist in the determinants of the capital structure. 3) Macro-economic variables more significantly affect the sensitivity of the capital structure of high tech corporations than traditional corporations. 4) Business risk has positive/negative impacts on capital structure of high tech/traditional corporations, respectively. 5) Six features of corporations have the same impacts on both high tech and traditional corporations, namely: firm size (+), growth opportunities (+), profitability (-), collateral value (+), non-debt tax shield (-), and dividend policy (-). In optimizing capital structure, the following policy implications can be dra wn for any company based on the results of this study: l Larger corporations can borrow more than small corporations, and thus enjoy the benefit of greater financial leverage. l Corporations with higher growth opportunities need to borrow more to meet their capital needs. l Corporations with higher profitability need to borrow less to meet their capital needs. l Corporations with higher collateral value (fixed assets) can borrow more than those with lower collateral value. l Increased non-debt tax shield will lower the tax benefits of financial leverage and hence reduce incentives for borrowing. l Corporations with higher cash dividend payments generally borrow less than corporations with lower cash dividend payments. Managers can apply the analytical results above to optimize capital structure and maximize firm value

Estimates of total fuel consumption in transporting grain from Iowa to major grain-importing countries by alternative modes and routes

Previous fuel consumption studies for rail, truck, and barge freight transport are based on industry averages over all commodities. The conflicting results from these studies are of limited usefulness in predicting total fuel consumption and fuel costs for individual grain shipments. This study measured fuel consumption in transporting grain from Iowa origins to Japan and Amsterdam by alternative routes and modes of transport and applied these data to construct equations for fuel consumption from Iowa origins to alternative final destinations.https://lib.dr.iastate.edu/specialreports/1086/thumbnail.jp

The cost structure of U.S. railroad industry, 1980-81

The proposed Coal Rate Guidelines published by the Interstate Commerce Commission imply that the railroad industry can raise rates on the so called "captive" coal to achieve the goal of revenue adequacy. Revenue adequacy is defined as a level of earnings sufficient to enable a carrier to meet all of its expenses, retire a reasonable amount of debt, cover plant depreciation and obsolescence, and earn a return on investment adequate to attract new capital. If the proposed Coal Rate Guidelines are implemented on coal traffic, it is expected that similar guidelines will be applied to other so called "captive" commodities, such as grains, fertilizers, chemicals, and agricultural products. The proposed Guidelines emphasize the inelastic demand for railroad transportation of "captive" coal, but ignore the cost side and the structures of the railroad industry as a crucial part in achieving railroad revenue adequacy;To estimate the potential in achieving the goal of revenue adequacy of the railroad industry from a cost saving point of view, two flexible functional forms, the translog and generalized Leontief models were used to estimate cost behavior under different scenarios. The results indicate that: (1) the railroad industry has substantial returns to traffic density and to average length of haul; (2) the railroad industry has small returns to firm size; (3) the net effects of returns to density, length of haul, and firm size are large and positive; (4) capital and labor are highly substitutable while labor and fuel, and capital and fuel are less substitutable; (5) labor costs are the major component of total costs; (6) all input price elasticities of demand are less than unity; (7) the railroad industry had excess capacity in 1980-81; (8) a cost saving policy can, in part, achieve the goal of revenue adequacy for the railroad industry in 1980-81;This study is based on 1980-81 Class I railroad data, hence the interpretation of the results is limited to the cost structure of these years. As the railroad industry has experienced rapid technological change, further research may be needed when new data become available. Moreover, the model specification can be further improved if less aggregate data are available.</p

Measurement of the Matching Degree between the Structure of China’s High-tech Industry and of Technological Resources Input

Based on general principles of welfare economics, a structure deviation index is constructed for the industry structure and the technological resources input structure. Taking China’s high-tech manufacturing and high-tech service industry from 2004 to 2013 as samples, the research measures the matching degree of the industry structure and the technological resources input structure between hightech manufacturing and high-tech service industry, among high-tech manufacturing sub-industries, and between two high-tech service sub-sectors, respectively. Conclusions are (i) allocation of technological resources between high-tech manufacturing and high-tech service industry is basically efficient; (ii)technological resources efficiency of high-tech manufacturing sub-industries exhibits gradientdifferences; (iii) information transfer, software and information technology services demonstrates longterm and absolute advantages

Estimates of total fuel consumption in transporting grain from Iowa to major grain-importing countries by alternative modes and routes

Previous fuel consumption studies for rail, truck, and barge freight transport are based on industry averages over all commodities. The conflicting results from these studies are of limited usefulness in predicting total fuel consumption and fuel costs for individual grain shipments. This study measured fuel consumption in transporting grain from Iowa origins to Japan and Amsterdam by alternative routes and modes of transport and applied these data to construct equations for fuel consumption from Iowa origins to alternative final destinations.</p