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

Empirical Techniques in Econometrics - Essay ExampleEconometrics is the application of statistical methods for firmness the financial issues. It has many applications like the effect of the economic conditions on the financial markets, the asset price derivations, predicting the future financial variables and other financial decision-makings. In econometrics thither is a lack of adequate test data for applying the particular methodology, this is termed as the small samples problem. There are further constraints in Econometrics with respect to data revisions and the standard 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 frequence 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 keep on ever-changing every day, hour , minutes and so on. So to have precise knowledge of these prices one needs to have large quantum of data, in tens of thousands or in millions. monetary data are very noisy in the sense that it is highly difficult to draw a certain pattern or trend from the accessible 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, set of financial variables.... sections, e.g. the weekly prices of mid 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 constant value or a linear trend. The stationary processes has a base tendency of moving around a linear value i.e. the mean value and its fluctuation from this value is termed as the deviation. The variables such as employment, asset p rices, megascopic domestic product follow a nonstationarity property and possess stochastic trends.Consider the trend in the financial return series like the vagabond of change of daily exchange 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 naive linear regression.Clive Granger (1981) proposed a solution to the time series by a simple regression equation (1)where, = dependent variable = single exogenic regressor = white noiseTo stress the solution, Granger defined the degree of integaration of the variable. Suppose a variable can be made nearly stationary by differencing it d times, thus 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 important exception, if I(0) then I(0). The linear combination, holds same statistical properties as an I(0) variable. This