Econometrics PDF

**Econometrics** What is econometrics? *Econometrics* means measurement (the meaning of the Greek word metrics) in economics. It includes all those statistical and mathematical techniques that are utilized in the analysis of economic data. The main aim of using those tools is to prove or disprove...

**Econometrics** What is econometrics? *Econometrics* means measurement (the meaning of the Greek word metrics) in economics. It includes all those statistical and mathematical techniques that are utilized in the analysis of economic data. The main aim of using those tools is to prove or disprove particular economic propositions and models. *Econometrics* may be defined as the quantitative analysis of actual economic phenomena based on the concurrent development of theory and observation, related by appropriate methods of inferences. *Econometrics* may also be defined as the social sciences in which the tools of economic theory, mathematics and statistical inference are applied to the analysis of economic phenomena. *Econometrics* is concerned with the empirical determination of economic laws. *Econometrics*, the result of a certain outlook on the role of economics consists of the application of mathematical statistics to economic data to tend empirical support to the models constructed by mathematical economics and to obtain numerical results. Based on the definition above, econometrics is an amalgam of economic theory, mathematical economics, economic statistics and mathematical statistics. However, the course (Econometrics) deserves to be studied in its own right for the following reasons: 1\. Economic theory makes statements or hypotheses that are mostly qualitative in nature. For example, microeconomics they state that, other thing remaining the same, a reduction in the price of a commodity is expected to increase the quantity demanded of that commodity. Thus, economic theory postulates a negative or inverse relationship between the price and quantity demanded of a commodity. But the theory itself does not provide any numerical measure of the relationship between the two; that is, it does not tell by how much the quantity will go up or down as a result of a certain change in the price of the commodity. It is the job of econometrician to provide such numerical estimates. Stated differently, econometrics gives empirical content to most economic theory. 2\. The main concern of mathematical economics is to express economic theory in mathematical form (equation) without regard to measurability or mainly interested in the empirical verification of the theory. Econometrics, as noted in our discussion above, is mainly interested in the empirical verification of economic theory. As we shall see in this course later on, the econometrician often uses the mathematical equations proposed by the mathematical economist but puts these equations in such a form that they lend themselves to empirical testing and this conversion of mathematical and practical skill. 3\. Economic statistics is mainly concerned with collecting, processing and presenting economic data in the form of charts and tables. These are the jobs of the economic statistician. It is he or she who is primarily responsible for collecting data on gross national product (GNP) employment, unemployment, price etc. the data on thus collected constitute the raw data for econometric work, but the economic statistician does not go any further, not being concerned with using the collected data to test economic theories and one who does that becomes an econometrician. 4\. Although mathematical statistics provides many tools used in the trade, the econometrician often needs special methods in view of the unique nature of the most economic data, namely, that the data are not generated as the result of a controlled experiment. The econometrician, like the meteorologist, generally depends on data that cannot be controlled directly. **Levels of measurement** refer to the different ways that variables can be quantified or categorized in research. Understanding these levels helps determine the appropriate statistical analysis to use. There are four main levels of measurement: **nominal, ordinal, interval,** and **ratio**. **1. Nominal Level. It** categorizes data without any order or ranking. The categories are mutually exclusive and exhaustive, meaning each data point can only belong to one category, and all possible categories are included. - **Example**: - **Gender**: Categories could be \"Male,\" \"Female,\" and \"Other.\" - **Type of Fruit**: Categories could be \"Apple,\" \"Banana,\" \"Orange,\" etc. The numbers or labels assigned to categories have no mathematical meaning; they simply identify different groups. **2. Ordinal Level.** Ordinal measurement categorizes data with a clear order or ranking, but the intervals between the ranks are not necessarily equal or known. - **Example**: - **Class Rank**: 1st place, 2nd place, 3rd place, etc. - **Satisfaction Level**: \"Very Unsatisfied,\" \"Unsatisfied,\" \"Neutral,\" \"Satisfied,\" \"Very Satisfied.\" You can say one category is higher or lower than another, but you can\'t quantify the exact difference between them. **3. Interval Level.** Interval measurement involves ordered categories with equal intervals between them, but there is no true zero point (zero does not indicate the absence of the variable). - **Example**: - **Temperature** in Celsius or Fahrenheit: The difference between 20°C and 30°C is the same as between 30°C and 40°C, but 0°C does not mean \"no temperature.\" - **IQ Scores**: The difference between IQ scores of 100 and 110 is the same as between 110 and 120, but there is no true zero IQ. You can measure the exact difference between values, but you cannot make meaningful statements about how many times greater one value is than another. **4. Ratio Level.** Ratio measurement has all the properties of interval measurement, but it also includes a true zero point, which means you can say something has none of the variable being measured. - **Example**: - **Height**: 0 cm means no height, and someone who is 180 cm tall is twice as tall as someone who is 90 cm. - **Weight**: 20 kg is twice as heavy as 10 kg. - **Income**: 0 income means no income, and an income of 50,000 is twice as much as 25,000. Ratios of measurements are meaningful; you can say one value is twice as much or half as much as another. **Types of Data** *1. **A [time series](https://en.wikipedia.org/wiki/Time_series)** is a series of [data points](https://en.wikipedia.org/wiki/Data_point) indexed (or listed or graphed) in time order. Most commonly, a time series is a [sequence](https://en.wikipedia.org/wiki/Sequence) taken at successive equally spaced points in time.* *Example.* Time GDP (in Billion) ------ ------------------ 2015 503.5 2016 677.1 2017 698.1 2018 789.5 2019 790.0 2020 799.8 2021 821.5 2\. **A cross-section** data collected by observing many subjects at the same point of time, or without regard to differences in time. Example.  3\. **Panel data** are multi-dimensional data involving measurements over time for the same subjects. Example.