Granger Causality Test To Study Causal Relationships Finance Essay - Free Essay Example

Sample details Pages: 4 Words: 1276 Downloads: 8 Date added: 2017/06/26 Category Finance Essay Type Cause and effect essay Did you like this example? SME, self-employed and business ownership are used interchangeably in our context. There are many definitions for SME and according to SPRING Singapore; an SME refers to enterprises with fixed asset investment of lesser than S$15 million for manufacturing sector and less than 200 employees for non-manufacturing sectors. There is little published information on business ownership and SMEs in Singapore. The only statistics on the rate of start-ups of business and companies are available in the Yearbook of Statistics (Tan, 2002). As such, we use the number of business formed and the number of companies formed to proxy business ownership and self employment. We also generate a series, named STARTUPS using the sum of companies and businesses. Don’t waste time! Our writers will create an original "Granger Causality Test To Study Causal Relationships Finance Essay" essay for you Create order STARTUPS = FORM_BUS + FORM_COMP Annual time series of formation of businesses and formation of companies from 1990 to 2009 are obtained from the Singapore Yearbook of Statistics. Business refers to a business firm, operating either as a sole-proprietorship or a partnership. It may be set up by individuals or companies. A company refers to a business entity registered under the Companies Act, Chapter 50. It has a legal personality (i.e. it has the right to own properties, it has perpetual succession and it can sue or be sued in its own name). It usually has the words Pte Ltd or Ltd as part of its name. Annual average unemployment rates, annual GDP and per capita GDP of these 20 years are also obtained from Department of Statistics, Singapore. 4.2 Methodology In regression model, existence of relationship between variables does not prove causality. In this paper we will use the Granger Causality test (Geweke, 1982, 1984; Geweke, Meese, Dent, 1983; C.W.J. Granger, 1969) to study causal relationships. The Granger Causality test is a statistical hypothesis test used to determine if one series can be used to forecast another. Unlike the classical linear regression model which shows only correlation, this test can reveal causality. The Granger Causality test is more preferred to Sims Causality Test as the Sims test uses more regressors, leading to a bigger loss of degree of freedom (Sims, 1980). The Vector Autoregression (VAR) model is usually used in Granger Causality due to its simplicity. 4.2.1 Unit Root Test Granger causality tests are only strictly valid for stationary series[1]and should therefore be preceded by a check of the order of integration of the variables, i.e. whether the data generating processes show a unit root or not. Many economic time series are not stationary at the levels (Nelson Plosser, 1982). As a first step, we used the Dickey Fuller (DF) unit root test (Dickey Fuller, 1979). If a series is non stationary in their level forms but is stationary in its first differenced form, we say the series is integrated of order 1. As the Granger Causality test follows the result of this unit root test, it is important to correctly determine this step. Hence we also performed an alternative unit root test, the Philips Perron test which is a generalized ADF test allowing autocorrelated residuals (Phillips Perron, 1988). 4.2.2 Cointegration Test Before performing Granger Causality Test on the series, cointegration tests are first carried out to test if there exist long run relationships between the variables. If two series are cointegrated, it means that at any point in time the two variables may drift apart, but there will always be a tendency for them to retain a reasonable proximity to each other. Following Granger and Lin (1995), two integrated series cannot cause each other in the long run unless they are cointegrated, in which case the Granger Causality will have to be tested using Vector Error Correction model (VECM). Cointegration test are only carried out on pairs of series that are non-stationary and are both integrated of the same order. In this paper, we will perform the Engel-Granger cointegration test (Engle Granger, 1987). A linear combination of two variables, Yt and Xt can be estimated from the following regression: Yt= ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²1 + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²2Xt + et Taking the residuals: t = Yt 1 2Xt If t is stationary, then the variables Yt and Xt are said to be cointegrated. Unit root test on this residual is carried out to check the order of integration. It is also noted that because t is residual we do not include a constant nor a time trend when performing the unit root test. Engle and Granger (1987) also point out that the critical values are different from that of Fuller (1976). 4.2.3 Constructing VAR Equations In Audretsch, Carrie and Thurik (2001), the following VAR equations are estimated using panel data of OECD countries from 1974 to 1998. Ut Ut-L = ÃÆ'Ã… ½Ãƒâ€šÃ‚ ± + j (Et-jL Et-(j+1)L) + j (Ut-jL-Ut-(j+1)L) + ÃÆ'†°Ãƒ ¢Ã¢â€š ¬Ã‚ º1t (1) Et Et-L = ÃÆ'Ã… ½Ãƒâ€šÃ‚ º + j (Ut-jL Ut-(j+1)L) + j (Et-jL-Et-(j+1)L) + ÃÆ'†°Ãƒ ¢Ã¢â€š ¬Ã‚ º2t (2) where U = unemployment rate, E = entrepreneurship represented by self-employment rate ÃÆ'†°Ãƒ ¢Ã¢â€š ¬Ã‚ º = random error such that ÃÆ'†°Ãƒ ¢Ã¢â€š ¬Ã‚ º ÃÆ' ¢Ãƒ ¢Ã¢â€š ¬Ã‚ °Ãƒâ€¹Ã¢â‚¬   N (0, ÃÆ' ¢Ãƒâ€¹Ã¢â‚¬  Ãƒ ¢Ã¢â€š ¬Ã‹Å") L = time span in the number of years J = number of time lags included. In (1), the lagged endogenous unemployment variables are added into the equation to correct for autocorrelation of unemployment growth over time. A negative coefficient ÃÆ'Ã… ½Ãƒâ€šÃ‚ ² is found, showing a clear Schumpeter effect of entrepreneurship reducing unemployment. Coefficient c is also negative, suggesting cyclical effect related to influence of policy measure. Similarly, we would like to examine these equations in the context of Singapore. For these OECD countries, Audretsch et al (2001) use a L=4 time span. On the other hand, Golpe van Stel (2007) use a L=2 time span in estimating this relationship in Spain. These time span is used as the impact of self employment on unemployment rate is not instantaneous; it requires a few year for firms to grow and if likely to contribute to the economy. In view of unemployment, it is also likely that people take time to make mental preparation before deciding to be self-employed. Before constructing the model, we will first determine the suitable length of time span, L for Singapore. We start by constructing simple VAR models with J=1 lag for each proxy of business ownership (start-ups, formation of business and formation of companies) to determine the optimal L. We estimate the following equations and select the best model using model selection criterion. Table 1: Estimating VAR models of J=1 L Equation 1 Ut Ut-1 = ÃÆ'Ã… ½Ãƒâ€šÃ‚ ± + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ² (Et-1 Et-2) + c (Ut-1 Ut-2) + ÃÆ'†°Ãƒ ¢Ã¢â€š ¬Ã‚ º1t Et Et-1 = ÃÆ'Ã… ½Ãƒâ€šÃ‚ º + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ³ (Ut-1 Ut-2) + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ¼ (Et-1-Et-2) + ÃÆ'†°Ãƒ ¢Ã¢â€š ¬Ã‚ º2t 2 Ut Ut-2 = ÃÆ'Ã… ½Ãƒâ€šÃ‚ ± + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ² (Et-2 Et-4) + c (Ut-2 Ut-4) + ÃÆ'†°Ãƒ ¢Ã¢â€š ¬Ã‚ º1t Et Et-2 = ÃÆ'Ã… ½Ãƒâ€šÃ‚ º + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ³ (Ut-2 Ut-4) + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ¼ (Et-2-Et-4) + ÃÆ'†°Ãƒ ¢Ã¢â€š ¬Ã‚ º2t 3 Ut Ut-3 = ÃÆ'Ã… ½Ãƒâ€šÃ‚ ± + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ² (Et-3 Et-6) + c (Ut-3 Ut-6) + ÃÆ'†°Ãƒ ¢Ã¢â€š ¬Ã‚ º1t Et Et-3 = ÃÆ'Ã… ½Ãƒâ€šÃ‚ º + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ³ (Ut-3 Ut-6) + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ¼ (Et-3-Et-6) + ÃÆ'†°Ãƒ ¢Ã¢â€š ¬Ã‚ º2t 4 Ut Ut-4 = ÃÆ'Ã… ½Ãƒâ€šÃ‚ ± + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ² (Et-4 Et-8) + c (Ut-4 Ut-8) + ÃÆ'†°Ãƒ ¢Ã¢â€š ¬Ã‚ º1t Et Et-4 = ÃÆ'Ã… ½Ãƒâ€šÃ‚ º + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ³ (Ut-4 Ut-8) + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ¼ (Et-4-Et-8) + ÃÆ'†°Ãƒ ¢Ã¢â€š ¬Ã‚ º2t As the VAR model is only valid for stationary series, we confirmed the stationarity of all Ut Ut-L and Et Et-L series of these model by performing unit root test. Detailed results of both the ADF test and PP test can be found in Table 3A and 3B (Appendix A). After determining the optimal L*, we construct equation (1) and (2) with variation in J=1,2 and 3 to choose the best number of lagged terms to be included in the model to describe this causal relationship. Granger causality test is then run on these models. Similarly, we construct VAR model as in equation (1) and (2) to investigate the causal relationship between Singapores business start-ups and economic growth. U is replaced with Y to represent annual GDP. U in equation (1) and (2) is then replaced with X, representing GDP Per Capita. Statistical package, EViews 6.0 which has built in unit root test will be used to carry out the analysis. Representation of all series in EVIEWS is shown in Table 2 of Appendix A.

Collaborative Essay - 1017 Words

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Explain with examples how the theoretical perspective of the researcher accepts choice of method Free Essays

The choice of method used to collect data is used by the theory that the given sociologist accepts. Most sociological theories have certain types of data they tend to collect, and certain methods that they choose to adopt. The two techniques used are quantitative and qualitative. We will write a custom essay sample on Explain with examples how the theoretical perspective of the researcher accepts choice of method or any similar topic only for you Order Now Quantitative techniques are used to measure distribution and the extent of a social characteristic. This technique is also useful when comparing two social variables such as social class and educational achievement. The technique provides a percentage or numerical feedback, allowing a statistical approach to sociological research. This type of research relies heavily on secondary data, i.e. research not collected by other parties, such as official statistics and social surveys, especially ones involving a formal interview. The Quantitative research technique is favoured highly by positivists who see measurement and statistics as a crucial element in making sociology more scientific. This technique can easily be duplicated, repeated and classified to achieve the same results, meaning the conclusion can be confirmed as fact. Positivists may also create their own primary material through creating questionnaires or structured interviews. The second research technique is Qualitative. Qualitative research is not based on measurements or statistics, and is useful if the researcher does not require a quantified figure or if the subject that is being studied cant be precisely measured. This style works well with participant observation as the observer may want to simply observe behaviour rather than record it. Interpretivists prefer the Qualitative technique as they employ methods such as in depth interviews, non-participant and participant observation. These methods are not easily repeated and no two observations may be the same, but that are still very valid. Traditionally, those who followed positivism were the Structuralists, the Functionalists and to a certain degree the Marxists. The Structuralists believe that the system of society took greater precedence than the elements within the system, so individuals are directed by society. Functionalists like Durkheim and Parsons believed that the actions of the individuals in society were controlled by the cultural system that they belonged to. Marx tried to apply more generalised historical social laws to his theories to try and predict society’s future. However, some positivists have criticised him for not being scientific enough, and claim that his ideas are merely theoretical. The main body of interpretivism is made up of Phenomenologists and ethnomethodoligists. Phenomenologists are concerned with understanding how humans understand their environment and the world around them. The distinction between Phenomenology and positivism is often exaggerated. For example, Durkheim, the founding father of Functionalism did not stick rigidly to his own methodology. He made mental sketches of what it was like to be a Roman Catholic or Protestant. Ethnomethodology looks at how humans categorise the world around them, how people give meaning to their social world. This approach is only concerned with the subjective approach. Some sociologists do not fit directly into a category, interpretivist or positive. Symbolic interactionists such as Becker are commonly described as interpretivists as they understand they must appreciate the point of view of the actor, nevertheless, they still try to maintain a casual relationships. Some develop hypotheses and assess these against further evidence. Another example of a sociologist who crossed the boundaries was Cicourel, and ethnomethodoligist also used statistics to study juvenile justice. In modern times, theoretical commitment is not seen as important as structure and action and a mixed of methods is employed. For example Lea and Young have both used in depth interviews and statistics when analysing crime. Important points to take into consideration are that some techniques are better at analysing phenomenon than others. For example you would have great difficulty using social survey or official statistics to study police brutality or new age travellers. Some methods may be rejected as unethical such as covert participant research. Practical considerations are also noted. Time, money and number of collaborators may be affected if research is funded by a particular body. In conclusion, tradition dictates that there are only two choices of research technique that are adopted by different social theories, but in reality however, many sociologists find that the best way to achieve reliable and valid results is by combining both qualitative and quantitative. How to cite Explain with examples how the theoretical perspective of the researcher accepts choice of method, Papers