Macro-Trends in Steel Industry in India: Implications for Risk

This paper presents a macro level analysis of steel industry. We have estimated the growth trend for production, consumption, exports and imports at the economy level by using a semi-log equation model. Firstly, we found that all variables are significantly related to a catch-all variable called ‘time’. Secondly, we calculated the predicted value of all variables and compared them with the actual value by the graphic presentations. They closely follow each other in most cases. The regression analysis shows that production grew at 8% and consumption at 7.75 during the time period 1992-2015. Exports grew at 9.78% per annum and declined drastically after the year 2005. On the other hand, the imports grew at 10.53% and increased also drastically after 2005. It shows that after the year 2005, there could have been a change in the industrial policy. On the whole we concluded that production and consumption increased over the time. Exports and imports show an increasing trend but export trend is weaker than the import trend. This shows that systematic risk arises due to transaction exposure of volatility in foreign exchange because we earned less Foreign Exchange (FE) and spent more on steel import in the form of Foreign Exchange. Since the time when FE rate regime has been liberalised the FE rates have been very volatile and Rupee has been depreciating constantly. If a larger sum is spent on imports it implies that the foreign exchange risk is higher. But since this is systematic risk it cannot be diversified.

Real Wage Rate And Productivity Relationship In The Declining U.S. Steel Industry

This study examines the relationship between the real wage rate and productivity in the U.S. steel industry in the critical period of 1963-1988. This period witnessed a declining steel output and employment, increasing productivity, and a slight increasing real wage rate. The severity of the decline was felt in the 1980s. The popular explanation focuses on the nominal wage rate relative to productivity (non-nominal value). The study is based on high-frequency monthly data set on output, employment, productivity, wage rate, factor prices, and national unemployment rate. Also control factors are constructed for the steel import protection and non-protection regimes. Some econometric modeling issues are addressed. Recognizing that productivity is stochastic and is potentially an endogenous variable, it is instrumented with a set of productivity-related variables including controls for various steel protection and non-protection regimes. Third, the wage in the industry is modeled as a function of exogenous productivity, price of steel products, national unemployment rate, and real interest rate. Serial correlation characterizes the data, and this is corrected with inter-temporal effect of the real wage rate, and with a differencing model. The main results of the study are threefold.First, OLS and Instrumental Variable (IV) estimates show that productivity is the key variable for explaining the real wage rate. Second, like in the literature, the study finds that heavy and autonomous capitalization has an impact on the rising productivity. Third, the study identifies an inter-temporal high real wage rate as the driving factor for explaining the short run real wage rate.These results are somewhat sensitive across specifications.

Real Wage Rate And Productivity Relationship In The Declining U.S. Steel Industry

This study examines the relationship between the real wage rate and productivity in the U.S. steel industry in the critical period of 1963-1988. This period witnessed a declining steel output and employment, increasing productivity, and a slight increasing real wage rate. The severity of the decline was felt in the 1980s. The popular explanation focuses on the nominal wage rate relative to productivity (non-nominal value). The study is based on high-frequency monthly data set on output, employment, productivity, wage rate, factor prices, and national unemployment rate. Also control factors are constructed for the steel import protection and non-protection regimes. Some econometric modeling issues are addressed. Recognizing that productivity is stochastic and is potentially an endogenous variable, it is instrumented with a set of productivity-related variables including controls for various steel protection and non-protection regimes. Third, the wage in the industry is modeled as a function of exogenous productivity, price of steel products, national unemployment rate, and real interest rate. Serial correlation characterizes the data, and this is corrected with inter-temporal effect of the real wage rate, and with a differencing model. The main results of the study are threefold.First, OLS and Instrumental Variable (IV) estimates show that productivity is the key variable for explaining the real wage rate. Second, like in the literature, the study finds that heavy and autonomous capitalization has an impact on the rising productivity. Third, the study identifies an inter-temporal high real wage rate as the driving factor for explaining the short run real wage rate.These results are somewhat sensitive across specifications.

A Comparative Cost Disadvantage Driven By Foreign Competition

This study focuses on the impact of foreign physical steel imports on the output of the US steel industry. This industry faces a comparative disadvantage in costs and from reduced utilized capacity in steel making. The strong desire of many foreign steel producers to export steel to the US lucrative market led to their plant modernization with the associated economies of scale. This led to steel import surge in America. The imposed trade restrictions had mixed outcomes. The domestic steel output is modeled as function of steel imports and from the size of the economy addressed by shipments. The OLS estimate of steel imports is insignificant and this could be explained by the ineffectiveness of the various instituted trade instruments, from increased foreign prices of steel, and from depreciated dollars at some points in time during the period in study. As expected the measure of the economyshipments variable has a positive impact on steel production.