A project Undertaken as Part of bsc (Hons) Economics with Finance degree, Westminster International University in Tashkent

Inflation

Inflation can partially affect companies’ performance; it may affect their performance and pricing behavior. To clarify if the firm believes that the inflation rate is too high they can easily increase the product or services price and not worrying regarding the public demand. But this scenario is feasible only for big companies but SMEs mostly suffer from inflation. There are costs that are changing the whole calculation for instance the wages increase and as a result, they cannot afford them anymore. Moreover, the investors prefer not to invest, as the inflation is not steady. On other hand, the inflation can reduce the debt amount for the firms by reducing the real value of debt. Besides, it will be much convenient to payback the old loans. In addition, it should be mentioned that inflation can be the cause of economic growth. In a country when the economy is growing, the inflation is a very predictable case thus; entrepreneurs will be motivated to start a business.

Base rate

Generally, the base rate is the interest rate that government sets for the local banks in order to land money to them. In a country with high interest rate, demotivate the entrepreneur to obtain a loan from bank as the interest rate is too high and it is a huge risk to work with such condition. However if the interest rate is low it gives the entrepreneurs courage to actualize the business plan. Because, when the government want to invest in businesses and develop enterprises they set the interest rate low to attract people and give them courage to start-up the idea. Therefore, the base rate and the entrepreneurship are related and has a negative relationship.

Model estimation

Normality test and the Granger causality tests have been used in this paper to check the statistical parameters of the data. As we know the non-stationary data that generate process for the majority of macro and microeconomics time series are characterized by unit root, thus we need to check for unit root firstly. The Augmented test by Dickie and Fuller (1979) and Philips Perron (1988) are the tests that we use to identify if the variable is stationary. Failure to reject the null hypothesis which is existence of unit root implies variable is non-stationary.
Another test that has been carried out is normality test, particularly Skewness-Kurtosis test. Normality is one of the main assumptions of OLS regresstion method. Error term must be bell shaped along all variables as well as there must not be multicollinearity among independent variables. Therefore we construct correlation matrix of variables. Moving forward we need to find and test the existence of one of these two unidirectional and bidirectional causality in granger sense.