Empirical Techniques in Econometrics Essay Example | Topics and Well Written Essays - 2500 words

Empirical Techniques in Econometrics - Essay ExampleEconometrics is the practical application of statistical methods for solving the financial issues. It has many applications like the effect of the economic conditions on the financial markets, the summation price derivations, predicting the future financial variables and other financial decision-makings. In econometrics there is a lack of comely test entropy for applying the particular methodology, this is termed as the small samples problem. There are further constraints in Econometrics with venerate to information revisions and the measurement error. These problems are generally faced due to the subsequent revisions in the reference data and the incorrect data estimation or incorrect measurement of data. The frequency of observation of the financial data has far-reaching implications. For the sake of understanding, just imagine the example of the prices of stocks in the share market, they are highly volatile and wield on c hanging e genuinely day, hour, minutes and so on. So to have precise knowledge of these prices single needs to have large quantum of data, in tens of thousands or in millions. Financial data are very noisy in the sense that it is highly difficult to draw a certain pattern or trend from the available data. In other sense the data doesnt have a specific distribution. But approximations are applied for modeling of the market and for analyzing the future trends, values of financial variables.... sections, e.g. the weekly prices of middle cap shares over the period of five years.Cointergration The macroeconomics and financial economics has empirical research based on time series. The macroeconomic time series has a nonstationarity property, which means that the variable doesnt return to a continuous value or a linear trend. The stationary processes has a basic tendency of moving near a linear value i.e. the mean value and its fluctuation from this value is termed as the deviation. T he variables such as employment, asset prices, gross domestic product follow a nonstationarity property and possess stochastic trends. cerebrate the trend in the financial return series like the rate of change of daily tack rate. The figure shows the volatility of returns. Fig.1Earlier it was a general practice to estimate nonstationary process equations in macroeconomic models by the simple linear regression.Clive Granger (1981) proposed a solution to the time series by a simple regression equation (1)where, = dependent variable = single exogenous regressor = white noiseTo distort the solution, Granger defined the degree of integaration of the variable. Suppose a variable can be made intimately stationary by differencing it d times, then it can be termed as integrated of order d or I(d). Stationary random variables are I(0).In equation (1), if I(1) and I(1), then I(1). But there exists an authorised exception, if I(0) then I(0). The linear combination, holds same statistical pr operties as an I(0) variable. This