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Econometrics_Ch_1

What is econometrics, the scope econometrics, data structure, econometrics methodology

Adisie
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Econometrics_Ch_1

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  1. Chapter One :Introduction to Econometrics By: Adisie T. ASU, Dep’t of Economics February 7, 2022 By: Adisie T. (ASU, Dep’t of Economics) Econometrics February 7, 2022 1/31

  2. Chapter Outline 1 Chapter Objective 2 Definition and Scope of Econometrics 3 Models: Economic models and Econometric models 4 The Types, Sources and Nature of Data 5 Methodology of Econometrics By: Adisie T. (ASU, Dep’t of Economics) Econometrics February 7, 2022 2/31

  3. 1.0. Chapter Objective After a successful completion of this chapter, you will I Define the term Econometrics I Understand the scope of Econometrics I Know the difference and relationship between economic model and econometric model. I Know the steps of econometrics analysis I Understand the different types of data that can be used for econometrics analysis By: Adisie T. (ASU, Dep’t of Economics) Econometrics February 7, 2022 3/31

  4. 1.1.Definition and Scope of Econometrics The literal meaning of econometrics is ’economic measure- ment”. It is the quantitative measurement and analysis of actual economic and business phenomena. Although economic measurement is an important concept, the scope of econometrics is much broader than economic mea- surement: Econometrics consists of the application of mathematical statis- tics to economic data to lend empirical support to the model con- structed by mathematical economics and to obtain numerical or quantitative results. By: Adisie T. (ASU, Dep’t of Economics) Econometrics February 7, 2022 4/31

  5. Econometrics is the quantitative analysis of actual economic phenomena based on the concurrent development of theory and observation(data), related by appropriate methods of inference. Econometrics is based upon the development of statistical meth- ods for estimating economic relationships, testing economic theories, and evaluating and implementing government and business policy. Econometrics uses Economic theory, mathematics and sta- tistical inferences to quantify of economic phenomena. By: Adisie T. (ASU, Dep’t of Economics) Econometrics February 7, 2022 5/31

  6. Economic theory makes statements or hypotheses that are mostly qualitative in nature (example: the law of demand), and mostly it does not provide any numerical measure of the relationship. This is the job of Econometrics. Mathematical economics is also neither concerned with mea- surement nor empirical verification of theory, rather simply fo- cuses on expressing economic theory in mathematical form or equations Similarly, economic data (economic statistics) is mainly con- cerned with collecting, processing, and presenting economic data. I It doesn’t go any further. The one who does that is Econometri- cians. By: Adisie T. (ASU, Dep’t of Economics) Econometrics February 7, 2022 6/31

  7. 1.2.Models: Economic models and Econometric models A model is a simplified representation, not every detail, of a real-world process. I It represents the salient features of the phenomena under study; I it should be simple enough to understand and complex enough to capture key information. An economic model is a simplified version of reality that allows us to observe, understand and make prediction about economic behavior. I does not claim to be able to predict the specific behavior of any individual or firm, but rather describes the average or systematic behavior of many individuals or firms. I consists of mathematical equations that describe various rela- tionships. By: Adisie T. (ASU, Dep’t of Economics) Econometrics February 7, 2022 7/31

  8. For example, according to Keynes theory of consumption, con- sumption is determined by income and the relationship can be expressed mathematically as Y = f (X) (1) Where; Y= consumption, X=income Mathematical models or equations are deterministic or exact or systematic in nature. I A relationship between two variables X and Y is deterministic or exact if for each value of variable X, there is one and only one corresponding values of variable Y. Equation 1 is exact or deterministic because once we specify the appropriate functional relationship between X and Y, we can ob- tain one and only one corresponding value of Y for a given value of X. By: Adisie T. (ASU, Dep’t of Economics) Econometrics February 7, 2022 8/31

  9. However, when studying individual consumption decisions, we observe different consumption expenditure with same in- come. That means, there are many other factors that affect con- sumption decision that we cannot even list, let alone observe, but we must somehow account for them. Therefore, the variable Y in general and consumption expenditure in particular is the sum of 1 The deterministic part,Y = f (X), which is the part of Y determined by X, and 2 The random and unpredictable part ?, which represents the part of Y that is not determined by X. Y = f (X) + ? By: Adisie T. (ASU, Dep’t of Economics) Econometrics February 7, 2022 9/31

  10. The term ?, sometimes represented by u, contains unobserved factors, such as the individual age, education, sex, errors in measuring consumption expenditure, wrong specification of the consumption function etc. We can incorporate some of these variables in the model,but we can never eliminate ? entirely. Therefore, in every econometric model, be it a consumption function, a supply equation, a production function, or anything else, there is a systematic or deterministic portion, f(X), and an unobservable random component, ?. By: Adisie T. (ASU, Dep’t of Economics) Econometrics February 7, 2022 10/31

  11. However, in any particular problem, one challenge is to deter- mine a functional form that is compatible with economic theory and the data. It needs paying due effort. The functional form represents a hypothesis about the relationship between the variables. In order to investigate the relationship between economic vari- ables, we must first build an economic model with the ap- propriate functional form and then a corresponding econo- metric model. By: Adisie T. (ASU, Dep’t of Economics) Econometrics February 7, 2022 11/31

  12. For instance, according to Keynes theory of consumption, con- sumption is a linear function of income. Thus, the mathematical expression of the economic model will be as follows Y = f (X) = β0+ β1X (2) The corresponding econometric model is Y = f (X) + ? = β0+ β1X + ? (3) The coefficients β0 and β1 are unknown parameters of the model that we estimate using economic data and an econo- metric technique. By: Adisie T. (ASU, Dep’t of Economics) Econometrics February 7, 2022 12/31

  13. Hence, an econometric model I is a simplified version of the real world process, explaining complex phenomena. I includes information regarding observed variables and disturbances. I consists of a set of equations, derived form economic theory, mathematical models and statistical tools that is regression. Regression is a method to determine the statistical relation- ship between a dependent variable (usually denoted by Y) and one or more independent variables (usually denoted by X). By: Adisie T. (ASU, Dep’t of Economics) Econometrics February 7, 2022 13/31

  14. A variable is any characteristic or attribute which is subject to change and can have more than one value I Age is a variable. It can take on many different values, such as 18, 49, 72, and so on. Gender is a variable. It can take on two different values, either male or female. I Sales volume, price, quantity demand, place,income, etc are also variables. They take on different values. An independent variable is variable that is presumed to influence other variable. A dependent variable is a variable that is affected by the independent variable. I For example, suppose you are interested in ”How income affect consumption expenditure?” I In this case, income is an independent variable that influence consumption and consumption is a dependent variable which is affected by income. By: Adisie T. (ASU, Dep’t of Economics) Econometrics February 7, 2022 14/31

  15. Independent variables also called explanatory, predictor, exoge- nous, regressor, control. Dependent variables also called explained, response, endoge- nous, regressand, outcome Variables can also be two kinds : I Quantitative Variables: are variables which is measured numerically and represent quantities or amounts with a standard units. • Examples: age,weight, income, price, consumption etc. I Qualitative/Categorical/indicator Variables:Variables take categories as their values such as • Example; Yes or No; color: red, blue, white, marital status; single married, widowed, divorced; preference: like or dislike. By: Adisie T. (ASU, Dep’t of Economics) Econometrics February 7, 2022 15/31

  16. There are two further kinds of quantitative variables: 1 Discrete(count) variables: variables with a finite number of values. Variables come from counting process. • Examples: number of children, students, chairs, bathrooms, houses etc. 2 Continuous variables: variable with an infinite number of val- ues. Variables come from measuring process. • Example: age, weight, temperature, income, exam score, etc. Under categorical variables there are two types of variables 1 Nominal Variable: It is a categorical of variable that is used to name, label or indicate particular attributes. There is no intrinsic ordering of these categories. • Example: Sex, marital status, region, color, occupation. 2 Ordinal Variable: It is a categorical variable for which the possible values are ordered. • Example: Academic rank: Instructor, assistant professor, as- sociate professor, professor; level satisfaction: very unsatisfied, unsatisfied, satisfied, very satisfied. By: Adisie T. (ASU, Dep’t of Economics) Econometrics February 7, 2022 16/31

  17. 1.3. The Types, Sources and Nature of Data In order to carry out an econometric research and conduct a sta- tistical inference, we must have data. Data are the different values associated with a variable. Based on the type of the variable, data can be: I Quantitative data such as prices or income that may be ex- pressed as numbers or some transformation of them, such as real prices or per capita income. or I Qualitative data- outcomes that are of an “either-or” situation. For example, a consumer either did or did not make a purchase of a particular good, or a person either is or is not married. Data may be collected at various levels of aggregation: I Micro data collected on individual economic decision-making units such as individuals, households, and firms. I Macro data resulting from a pooling or aggregating over individuals, households, or firms at the local, state, or national levels. By: Adisie T. (ASU, Dep’t of Economics) Econometrics February 7, 2022 17/31

  18. Data can be generated either experimental or non-experimental approach 1 Experimental data: are often collected in laboratory environ- ments in the natural sciences, but they are much more difficult to obtain in the social sciences. 2 Non-experimental data: are not accumulated through con- trolled experiments on individuals, firms, or segments of the econ- omy. • Example: Population survey, Households income and expenditure survey are good examples of non-experimental data. Economists and other social scientists work in a complex world in which data on variables are “observed” and rarely obtained from a controlled experiment. I This makes the task of learning about economic parameters all the more difficult. By: Adisie T. (ASU, Dep’t of Economics) Econometrics February 7, 2022 18/31

  19. Data can be obtained either from I Primary sources: primary data are the data which the researcher collects, for the very first time, from the original source through experiment, questionnaire, interview, mail, etc. • These data are also called first hand data. I Secondary sources: secondary data are data collected by any person,organization,or agency in the past through experimental or survey method, for some other purpose, but used by a researcher to to deal with some problem at hand. • These data type are called second hand data. Example; Data obtained from CSA, MoFED, WB, IMF, WDI, etc are secondary data. By: Adisie T. (ASU, Dep’t of Economics) Econometrics February 7, 2022 19/31

  20. Data, in general, and economic data, in particular may have either cross-sectional, time series, pooled, or panel nature. 1 Cross-sectional data I Consists of a sample of individuals, households, firms, countries, etc. taken at a given point in time I Each observation is a new individual, firm, etc. with information at a point in time. I We often assume that the data are obtained by random sam- pling from the underlying population. I Re-ordering of data doesn’t matter because it doesn’t take ‘pe- riod of time’ into account. By: Adisie T. (ASU, Dep’t of Economics) Econometrics February 7, 2022 20/31

  21. 2 A time series data I consists of observations on a variable or several variables over time. I Examples: stock prices, money supply, CPI, GDP, sales, inflation rate, unemployment rate etc. I Data frequency (usually daily, weekly, monthly, quarterly and annually) and ordering is important. By: Adisie T. (ASU, Dep’t of Economics) Econometrics February 7, 2022 21/31

  22. 3 Pooled cross-sections I Pooling cross sections from different years is often an effec- tive way of analyzing the effects of a new government policies, programs etc.(i.e.the before and after change). I As an example, consider the following data set on housing prices taken in 1993 and 1995, before and after a reduction in prop- erty taxes in 1994. I 250 randomly selected houses for 1993 and again 270 randomly selected houses for 1995. By: Adisie T. (ASU, Dep’t of Economics) Econometrics February 7, 2022 22/31

  23. 4 Panel or longitudinal data I consists of a time series for each cross-sectional member in the data set. I Same cross-sectional units (individuals, firms, or countries) are followed over a given time period I Example, suppose we have number murders and unemployment rate of 150 cites of a-year period. I While in pooled data the observations in each cross-section do not necessarily refer to the same unit, in panel data the same cross-sectional units observed at multiple points in time. By: Adisie T. (ASU, Dep’t of Economics) Econometrics February 7, 2022 23/31

  24. 1.4. Methodology of Econometrics To conduct an empirical economic study, we must follow the fol- lowing steps or methodology By: Adisie T. (ASU, Dep’t of Economics) Econometrics February 7, 2022 24/31

  25. 1 Statement of the Economic Theory or Hypothesis I The process begins with reviewing of the theory or hypothesis or situation under consideration. I This step includes defining the theory or hypothesis that needs to be tested and determining the variables for which the cause and effect relationship is to be conducted. I The hypothesis, at this point, only establishes qualitative relationship and does not offer any numeric relationships. I One example is the Marginal Propensity to Consume (MPC) proposed by Keynes. • He postulated that the MPC, the rate of change of consumption for a unit change in income is greater than zero but less than 1. I Therefore, a researcher should have to state clearly the hypothesized relationship between variables like Keynes did. By: Adisie T. (ASU, Dep’t of Economics) Econometrics February 7, 2022 25/31

  26. 2 Specification of the economic or mathematical model I Once we have set the hypothesis, we need to express economic theory or hypothesis in mathematical form using the appropriate functional form. I That means a mathematical model, for instance, for Keynes consumption theory as follows Y = f (X) = β0+ β1X ; 0 < β1< 1 (4) 3 Specification of the Econometric Model: In order to test the hypothesis, it’s essential to modify the mathematical expression of economic model into an econometric model as follow: Y = f (X) + ? = β0+ β1X + ? (5) I Where; Y = consumption expenditure and X = income β0= the intercept term β1= the slope coefficient. The slope coefficient β1measures the MPC. ? = the disturbance or error term. By: Adisie T. (ASU, Dep’t of Economics) Econometrics February 7, 2022 26/31

  27. Based on the nature and types of variables and data, we may have different econometric models. Some of these are 1 Linear regression:Includes simple, Multiple, and multivariate linear regressions 2 Binary choice models: Binary logit and probit. 3 Multiple choice models: Multinomial and ordered probit and logit, 4 Limited dependent variable models: Tobit, Truncated , and Heckman regression models. 5 Count data models: Possion, Negative binomial, and zero inflated models. 6 Time series models: Uni-variate and Multivariate Time series models. 7 Panel Models: Fixed and random effects model Therefore, using an appropriate econometric model for the case under investigation is important. By: Adisie T. (ASU, Dep’t of Economics) Econometrics February 7, 2022 27/31

  28. 4 Obtaining data I To estimate the econometric model that means to obtain numerical values for β0and β1, we need data. I The data can be obtained from primary or secondary sources. It can also be cross-section, time series or panel data. 5 Estimation of the econometric model I Here we obtain numerical values(estimates) for α and β. I Regression analysis is the main tool used to obtain the estimates. I Using this technique and the data taken from Gujarati’s text book, we obtain the following estimates of α and β, 184.08 and 0.7064, respectively. Thus, the estimated consumption function is: Y = 184.08 + 0.7064X + ? (6) By: Adisie T. (ASU, Dep’t of Economics) Econometrics February 7, 2022 28/31

  29. 6 Hypothesis Testing:it refers to a formal process of investigating a supposition or statement to accept or reject it. I If it is consistent with the hypothesis, it is accepted. Otherwise it is rejected. I Now we go back to the part where we had economic theory or hypothesis. That is to find out whether the estimates obtained in, equation 3 are in accord with the expectations of the theory that is being tested. I Keynes expected the MPC to be positive but less than 1 and we found the MPC to be about 0.70. I But before we accept this finding as confirmation of Keynesian consumption theory, we must enquire whether this estimate is sufficiently below one. I In other words, is 0.70 statistically less than 1? If it is, it may support Keynes’ theory. To know this, we need to use either T-test or P-value. By: Adisie T. (ASU, Dep’t of Economics) Econometrics February 7, 2022 29/31

  30. 7 Forecasting or prediction: I If the chosen model does not refute the hypothesis or theory under consideration, we may use it to predict the future value of the dependent or forecast variable Y on the basis of the known or expected future value of the explanatory or predictor, variable X. I For example, if the hypothesis testing for the theory of consumption was concluded to be correct, we forecast the values of the consumption by specifying the values of income (GDP). I You will answer questions like, how much would a country or household or individual consumption expenditure for some specified amount of income(GDP) ? By: Adisie T. (ASU, Dep’t of Economics) Econometrics February 7, 2022 30/31

  31. 8 Use of models for control or policy purpose I Lastly, if the theory seems to make sense and the econometric model was not refuted on the basis of the hypothesis test, we can go on to use the theory for policy recommendation or decision making . I If your theory is really good, then maybe you will earn the Nobel Prize of Economics. The end!!! By: Adisie T. (ASU, Dep’t of Economics) Econometrics February 7, 2022 31/31

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