class: center, middle, inverse, title-slide .title[ # .b[What is Econometrics?] ] .subtitle[ ## .b[.green[EC 339]] ] .author[ ### Marcio Santetti ] .date[ ### Fall 2022 ] --- class: inverse, middle # Prologue --- # The role of expectations <br> What can you expect from this course? -- <br> .pull-left[ - What we .hi[will] do - .can-edit[] - .can-edit[] - .can-edit[] - .can-edit[] ] .pull-right[ - What we .hi[will not] do - .can-edit[] - .can-edit[] - .can-edit[] - .can-edit[] ] --- # Why is this course important for you? Being able to make .hi[sense] of (economic) data is one of the most important .hi[skills] you may develop in your Major field. -- - .hi-orange[Job market] (.mono[Stata/R/Python] are highly valued!) - Further .hi[academic] studies -- <br> When you can estimate with your own fingers (.hi-orange[???]) and see with your own eyes a .hi[downward-sloping demand curve], for example -- - .hi-orange[Empowerment] - A more comprehensive learning --- # Is this course hard? -- What does an Economist always have as a .hi[standard answer]? -- - It .hi-orange[depends]! -- <br><br> Learning Econometrics is quite a .hi[journey] -- <br> - But well worth it! - Will not be exhausted with this course - Here, a nicer challenge (theory and practice) - The instructor is here to _.hi[help]_ you --- # Is this course hard? - In summary: -- - Take this course _.hi[seriously]_ - Come to class .hi-orange[in time] and with an .hi[open mind] - Ask .hi-orange[questions] - Do the .hi[assignments] - .hi-orange[Exams] will reflect what assignments (esp. _Problem Sets_) have asked you -- <br> - About .mono[Stata] -- - It may take some .hi[time] to feel comfortable with it - But after a few weeks, it will become a .hi-orange[good friend] - Feed it well and it will be fine! --- # Some practical tips <br><br> A friend's .hi-orange[advice]: -- - Create a .hi[folder] in your computer for this course. -- - .hi[Please]. -- - We will use .hi-orange[hundreds] of different files throughout the semester. - .hi[Organization] is key! - Even better: create folders for .hi-orange[each week]. It will make your life easier. --- layout: false class: inverse, middle # The nature of Econometrics --- # Defining Econometrics <br><br> Literally interpreted, Econometrics means “__.hi[economic measurement]__.” --- # The methodology of Econometrics The .hi["classical" workflow] of an econometrician goes along the following lines: 1\. Statement of .hi-orange[theory] or hypothesis; 2\. Specification of the .hi[mathematical model] of the theory; 3\. Specification of the statistical, or .hi-orange[econometric model]; 4\. Obtaining the .hi[data]; 5\. Estimation of the .hi-orange[parameters] of the econometric model; 6\. .hi[Hypothesis testing]; 7\. .hi-orange[Forecasting] or prediction; 8\. Using the model for control or .hi[policy] purposes. --- layout: false class: inverse, middle # A practical example --- # Engel's Law <br> As one's income .hi[rises], what happens to the .hi-orange[proportion] of income spent on food? <br> -- - In other words, how does the .hi[income elasticity] of demand for food behave with respect to food? -- <br><br> Ernst Engel (1821—1896) argued that food expenditures grow .hi-orange[less] than people's increases in income, _in percentage terms_. --- # Mathematical model <br><br><br> $$ Foodexp_i = b_0 + b_1Income_i $$ --- # Econometric model <br><br> $$ Foodexp_i = \beta_0 + \beta_1Income_i + u_i $$ -- <br> In _.hi[elasticity]_ terms: $$ log(Foodexp_i) = \beta_0 + \beta_1log(Income_i) + u_i $$ -- <br> Engel's _.hi-orange[hypothesis]_: `\(0 < \beta_1 < 1\)` --- # Obtaining data <br><br> [`Koenker and Bassett (1982)`](https://www.jstor.org/stable/1912528?seq=1#metadata_info_tab_contents) collected data on food expenditure and income for 235 Belgian working class households. --- # Fitting a linear model <img src="000-what-is-econometrics_files/figure-html/unnamed-chunk-2-1.svg" style="display: block; margin: auto;" /> --- # Fitting a linear model (cont.) <img src="000-what-is-econometrics_files/figure-html/unnamed-chunk-3-1.svg" style="display: block; margin: auto;" /> --- # Parameter estimation <br><br> $$ \widehat{log(Foodexp_i)^*} = 0.55 + 0.86\log(Income_i) $$ .footnote[ *: the "^" symbol means .hi[estimated]. ] --- # Econometric inference <br><br><br> <table style="border-collapse:collapse; border:none;"> <tr> <th style="border-top: double; text-align:center; font-style:normal; font-weight:bold; padding:0.2cm; text-align:left; "> </th> <th colspan="3" style="border-top: double; text-align:center; font-style:normal; font-weight:bold; padding:0.2cm; ">log(foodexp)</th> </tr> <tr> <td style=" text-align:center; border-bottom:1px solid; font-style:italic; font-weight:normal; text-align:left; ">Predictors</td> <td style=" text-align:center; border-bottom:1px solid; font-style:italic; font-weight:normal; ">Estimates</td> <td style=" text-align:center; border-bottom:1px solid; font-style:italic; font-weight:normal; ">CI</td> <td style=" text-align:center; border-bottom:1px solid; font-style:italic; font-weight:normal; ">p</td> </tr> <tr> <td style=" padding:0.2cm; text-align:left; vertical-align:top; text-align:left; ">(Intercept)</td> <td style=" padding:0.2cm; text-align:left; vertical-align:top; text-align:center; ">0.55</td> <td style=" padding:0.2cm; text-align:left; vertical-align:top; text-align:center; ">0.27 – 0.82</td> <td style=" padding:0.2cm; text-align:left; vertical-align:top; text-align:center; "><strong><0.001</strong></td> </tr> <tr> <td style=" padding:0.2cm; text-align:left; vertical-align:top; text-align:left; ">income [log]</td> <td style=" padding:0.2cm; text-align:left; vertical-align:top; text-align:center; ">0.86</td> <td style=" padding:0.2cm; text-align:left; vertical-align:top; text-align:center; ">0.82 – 0.90</td> <td style=" padding:0.2cm; text-align:left; vertical-align:top; text-align:center; "><strong><0.001</strong></td> </tr> <tr> <td style=" padding:0.2cm; text-align:left; vertical-align:top; text-align:left; padding-top:0.1cm; padding-bottom:0.1cm; border-top:1px solid;">Observations</td> <td style=" padding:0.2cm; text-align:left; vertical-align:top; padding-top:0.1cm; padding-bottom:0.1cm; text-align:left; border-top:1px solid;" colspan="3">235</td> </tr> <tr> <td style=" padding:0.2cm; text-align:left; vertical-align:top; text-align:left; padding-top:0.1cm; padding-bottom:0.1cm;">R<sup>2</sup> / R<sup>2</sup> adjusted</td> <td style=" padding:0.2cm; text-align:left; vertical-align:top; padding-top:0.1cm; padding-bottom:0.1cm; text-align:left;" colspan="3">0.884 / 0.883</td> </tr> </table> --- layout: false class: inverse, middle # The role of the computer --- # The role of the computer <br><br> > "Regression analysis, the bread-and-butter tool of econometrics, these days is _.hi[unthinkable]_ without the computer and some access to statistical software" <br> .right[(Gujarati, 2004, p. 13, emphasis added).] --- layout: false class: inverse, middle # Types of data --- # Types of data .hi[Cross-section data]: - Data on one or more variables, collected at the same point in time, for different or the same individuals (*i*). These individuals may be persons, states, countries, plants, firms, etc. - Census; - Opinion polls. -- .hi[Time series data]: - Set of observations on the value that a variable takes at different times (daily, monthly, quarterly, annually, etc.) - Daily: stock prices; - Monthly: CPI, unemployment rate; - Quarterly: GDP; - Annually: Government budgets. --- # Types of data (cont.) <br><br> .hi[Panel (longitudinal) data]: * Same (or different) cross-sectional units (*i*) is (are) surveyed over time (periodically). * Example: Housing Census by the US Department of Commerce. --- layout: false class: inverse, middle # Next time: Stats/Stata refresher --- exclude: true