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  • Prof. Victor Chernozhukov

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  • Econometrics

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Solve one of problems 1, 2, or 3 from Lecture 2 (PDF) and one of problems 4 or 5 from Lecture 2. You can use any econometric/statistical software you like. The data sets are posted below. Please provide detailed write-ups: explain theoretical foundations of your analysis and provide step-by-step explanation for your empirical analysis. Think that you are writing an empirical portion of your paper and you are trying to communicate the results to your colleagues and referees. We also provide R-code below (and a link to Stata code is also mentioned): you are welcome to take a look at the code, but you are not allowed to copy & paste the code—please write your own code. You can work in groups to discuss the homework, but all the write-ups and all the coding should be individual. 

Homework 2 Data Description (PDF)

Associated Files 

Data file for Homework 2 (CSV - 14.1MB)

Hint (R-code for AJR) (R)

Hint (R-code for AK) (R)

AJR Data in CSV form (TXT)

Stata code for Weak-Id robust inference is available from Christian Hansen’s website . You can take a look, but write your own code. We also provide R-code below: you are welcome to take a look at the code, but you are not allowed to copy and paste the code—please write your own code (to learn!)

MIT Open Learning

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Econometrics Application

Description of course goals and curriculum, learning from classroom instruction, learning for and from assignments, external resources, what students should know about this course for purposes of course selection.

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ECN 102 A01-A04:  ANALYSIS OF ECONOMICS DATA   SYLLABUS Department of Economics, University of California - Davis FALL 2022

Meeting: Tues Thurs 10.30 - 11.50 a.m. Wellman 126

Instructor Office Hours: Tuesday afternoon       3.30 - 5.00 pm in office SSH 1124   In person only Wednesday afternoon  3.30 - 5.00 pm  in office SSH 1124  In person plus zoom

Teaching Assistants:  

Kathya Tapia  [email protected]   Office hours: Wednesday 11.00 am - 1.00 pm in SSH 0120   In person only

Rebecca Brough  rjbrough @ucdavis.edu   Office hours: Monday 11.00 - 1.00 pm       in SSH 0120   In person only Discussion Sections in Hutchison 93: A01: Tuesday 1.10 - 2.00 pm  93 Hutchison   TA: Kathya Tapia A 02: Tues day 2.10 - 3.00 pm  93 Hutchison   TA: Kathya Tapia A 03: Tues day 3.10 - 4.00 pm  93 Hutchison   TA:  Rebecca Brough A04: Tues day 4.10 - 5.00 pm  93 Hutchison  TA: Rebecca Brough Course Goals:

Pre-requisites: Economics 1A-B, Statistics 13, 13Y or 32 and Math 16A-B or 17A-B or 21A-B or consent of instructor. The essential pre-requisites are exposure to introductory lower-division courses in economics and statistics. Relationship to Economics 140 Economics 140 (Econometrics) is a more advanced course that also covers the methods of Economics 102. Economics 140 has Economics 102 or Statistics 108 as a prerequisite. For more on possible data classes see http://cameron.econ.ucdavis.edu/e102/morestat.html Topical Outline by Lecture Number :

The text is A. Colin Cameron, Analysis of Economics Data: An Introduction to Econometrics. A. UNIVARIATE: Analysis of a single economics variable Lecture 1: Introduction and getting going on Stata  (chapter 1 + Stata http://cameron.econ.ucdavis.edu/stata/stata.html ). Lecture  2: Summarizing data using descriptive statistics and visualizing data using charts (chapter 2.1-2.6) Lecture  3: The sample mean (chapter 3.1-3.6 and appendix B) Lecture  4: Statistical inference based on the sample mean using estimation and confidence intervals (chapter 4.1-4.3) Lecture  5: Statistical inference based on the sample mean using hypothesis tests (chapter 4.4-4.7)

B. BIVARIATE REGRESSION: The relationship between two economic variables

Lecture  6: Bivariate data summary: scatter plots, correlation and regression (chapter 5.1-5.5) Lecture 7: ***** First midterm exam  ***** Lecture 8: Bivariate data summary: regression, goodness of fit (chapter 5.6-5.12) Lecture 9: The least squares estimator (chapter 6.1-6.4) Lecture 10: Statistical inference on regression coefficients (chapter 7.1-7.7) Lecture 11: Bivariate case studies (chapter 8.1) Lecture 12: Models with natural logarithms (chapter 9.1-9.6) Lecture 13: ***** Second midterm exam *****

A. Colin Cameron , Analysis of Economics Data: An Introduction to Econometrics. The text is available from Amazon for $25 paperback or $6.99 for a Kindle replica book. A Kindle replica book is just a pdf but requires downloading the Kindle App to your PC, Mac, Android or iOS. Copies of the text are also on Reserve at the Library.

Slides for the course text are available at http://cameron.econ.ucdavis.edu/aed/ The datasets and Stata programs used in the course text are at http://cameron.econ.ucdavis.edu/aed/

Additional Materials: The course Canvas site has assignments under Files/ Homeworks. Assignments should be uploaded to Canvas under Assignments. The website http://cameron.econ.ucdavis.edu/e102/e102.html has past exams and solutions and some links to Stata material. There are usually free tutors for 102: see http://economics.ucdavis.edu/undergrad-program/tutoring The Khan Academy has excellent video tutorials and exercises. See https://www.khanacademy.org/math/ap-statistics

Discussion Sections: These are held in a university computer lab in Hutchison 93.

Computer Materials:  Assignments use Stata . Stata is installed in 93 Hutchison, 2101 SCC, and the Virtual Lab (after 2060 SciLab closes - see https://virtuallab.ucdavis.edu ) To see whether 93 Hutchison and 2101 SCC are available see https://computerrooms.ucdavis.edu/available/ .   I strongly recommend purchasing Stata. It will make it much easier to implement and learn Stata. Stata can be purchased at https://www.stata.com/order/new/edu/gradplans/student-pricing/   Stata/BE is more than adequate and for a student license costs $48 (6 months), $94 (1 year); $225 (permanent copy). Note that ECN140 and some other courses such as ECN 132 also use Stata. Older versions of Stata are fine.

To install Stata after it is purchased: (1) Choose the correct operating system (e.g. Windows or Mac); (2) Choose the correct version of Stata - the student price version is Stata/IC; (3) When you first run Stata after installation it will ask for an "authorization code". These codes are given in a pdf attachment you will received in the email from Stata following purchase (some are lengthy and it is easiest to cut and paste them in).

  • Read the chapters in the text before lecture
  •   Come to lecture and take notes.
  •   Try the homework assignments on your own
  •   Go to discussion section where the TA will go over the homework and ask questions
  •   Do end-of-chapter exercises and past exams, again without looking at your notes.

Academic honesty is required - see below.

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Princeton University Library

Spi 508a: econometrics and public policy.

  • Library Databases
  • STATA Resources
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  • Citing Sources

Data and Statistical Services (DSS)

Data and Statistical Services (DSS) provides data and statistical consulting. The service is located in Firestone Library.

Experts are available to advise Princeton University student, faculty, and staff on choosing appropriate data, application of quantitative research methods, the interpretation of statistical analyses, data conversion, and data visualization. Subject specialists help choose appropriate data. The statistical packages supported by consultants are R/R Studio, Stata, and SPSS. We provide statistical and software assistance in quantitative analysis of electronic data as part of independent research projects, such as junior papers, senior theses, term papers, dissertations, and scholarly articles.*

* Please note: Students are welcome to use our online tutorials and computing services. DSS consultants, however, do not provide assistance with homework assignments, problem sets, or take-home exams.

Library Resources to Connect Econometrics with Stata code

  • Learn About Simple Regression in Stata With Data From the Consolidated State Performance Report (2012–2013) This dataset is designed for teaching simple regression. The dataset is a subset of data derived from the Consolidated State Performance Report from the U.S. Department of Education. It looks specifically at freshman graduation rates and courses taught by qualified teachers across the 50 U.S. states plus the District of Columbia and Puerto Rico. The dataset file is accompanied by a Teaching Guide, a Student Guide, and a How-to Guide for Stata. The Student Guide and data curation were done by the Odum Institute, and the How-to Guide was co-authored by Abigail-Kate Reid and Nick Allum.
  • Learn About Logistic Regression in Stata With Data From the American National Election Study (2012) This dataset is designed for teaching logistic regression. The dataset is a subset of data derived from the 2012 American National Election Study, and the example tests whether reported vote choice in the 2012 U.S. Presidential election is predicted by several factors, including a respondent’s race/ethnicity and how they feel about the Democratic and Republican Parties. The dataset file is accompanied by a Teaching Guide, a Student Guide, and a How-to Guide for Stata.
  • Learn About Logistic Regression in Stata With Data From the National Household Education Surveys Program, School Readiness Survey (2007) This dataset is designed for teaching logistics regression. The dataset is a subset of data derived from the 2007 School Readiness Survey, and the example examines whether or not young children know all or most of the letters of the alphabet, and whether that is predicted by their TV viewing, their age, and whether their parents read to them. The dataset file is accompanied by a Teaching Guide, a Student Guide, and a How-to Guide for Stata. The Student Guide and data curation was done by the Odum Institute; the How-to Guide was coauthored by Abigail-Kate Reid and Nick Allum.
  • Learn About Multiple Regression With Dummy Variables in Stata With Data From the General Social Survey (2012) This dataset is designed for teaching multiple regression with dummy variables. The dataset is a subset of data derived from the 2012 General Social Survey, and the example presents an analysis of whether a person’s weight is a linear function of a number of attributes, including whether the person is female and whether the person smokes cigarettes. The dataset file is accompanied by a Teaching Guide, a Student Guide, and a How-to Guide for Stata. The Student Guide and data curation were done by the Odum Institute, and the How-to Guide was co-authored by Abigail-Kate Reid and Nick Allum.
  • Learn About Ordered Probit in Stata With Data From the Cooperative Congressional Election Study (2012) This dataset is designed for teaching ordered probit. The dataset is a subset of data derived from the 2012 Cooperative Congressional Election Study (CCES), and the example presents an analysis of whether survey respondents believe that laws covering the sale of firearms should be more strict, kept as they are, or less strict. The dataset file is accompanied by a Teaching Guide, a Student Guide, and a How-to Guide for Stata. The Student Guide and data curation was done by the Odum Institute; the How-to Guide was coauthored by Abigail-Kate Reid and Nick Allum.
  • Case Study: Electoral Systems and Turnout: Evidence From a Regression Discontinuity Design (note: no code included) This case study will show you how to carry out a Regression Discontinuity Design by way of an example about voter turnout in elections. In 2002, municipalities in Poland were assigned to either a majoritarian or a proportional electoral system based on a population threshold of 20,000 inhabitants. This assignment by use of a population threshold introduces a discontinuity that splits practically identical municipalities into two groups, one group with a proportional electoral system and another group with a majoritarian electoral system. We will show you in this case study how to use this discontinuity to reliably and accurately estimate the effect of a change from a majoritarian to a proportional electoral system on voter turnout.

Relevant STATA books from the PUL catalog

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Regression Discontinuity workshop: Data and Stata .do file

  • Data file for Members of Parliament (MP) example
  • Stata .do file for MP example
  • Slides from 2/18 lecture
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Research Guides

ECON 203: Econometrics

Stata @ wellesley, organizing your data, helpful books.

  • Find Data Using IPUMS
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  • Class Activities - 203-02

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Stata is available for installation on student computers: PCs | Macs

HERE are instructions for installing Stata.

Stata is available on all classroom and lab computers on campus.

Want to use Stata off-campus? Install it on your laptop (while on campus), and then use the VPN to log in and access Stata off campus. Visit the VPN help page  for instructions.

For issues installing Stata or setting up the VPN, visit the Help Desk in Clapp Library or email [email protected]

Organizing Folders

  • Create a new folder for your class. Name it without spaces (e.g., ECON203-SP12).
  • Create 2 new folders in your class folder: one for assignments (Assignments) and one for your final project (Project).
  • Save your data files to the appropriate folders within your class folder.

Naming Files

-Adopt consistent file naming conventions!

-Name your files something that alludes to their content or purpose.

Example 1: Data for a class's second lab. Poor choice: mydata.dta Better name: lab2census.dta

Example 2: You download US census data for your final project for the year 2000; name it census00.dta. Then you create a subset containing only women ages 18-30; name it census00fem.dta.

-If you have multiple versions of the same file, add increasing numbers to the end of the file (e.g., census00v2, census00v3, etc). If you go back and make changes to an earlier version of the file, save a copy with the next highest number (e.g., census00v4).

Answers to the Top Stata Questions at Wellesley

  • Help! My Dataset Won’t Open!
  • How do I create dummy variables? How do I recode variables?
  • How do I combine two datasets?
  • When I run a regression, why do some of the variables and/or observations disappear from the output?
  • How do I run regressions with fixed effects?
  • How to Download World Bank Data and Open It in Stata

Converting Data to Stata Format

Use these tutorials to help you get your data into Stata.

Need to open other file formats in Stata? Contact Carolin for help!

  • From SAS or SPSS Format (.sas7bdat, .sd7, .sd2, .ssd01, .xpt, or .sav)
  • From Raw (.dat, .raw) Format
  • From Excel (.xls, .xlsx) or basic tables (.txt, .csv)

Saving Output Tables

Log Files - keep track of every command you run and all the results. Great way to keep a record of what you have done.

  • To start a new log: First change your working directory to the correct folder ( cd command). Then in the command box type log using "logname", text . Give your log file a usefulname such as 'Lab2Feb6.log.' Begin a new log file each time you begin working in Stata or use the append option to add on to an existing log file.
  • To view an existing log: You can open the file in any text editor or in Stata (type view logname.log ). This is helpful for remembering what you did from one session to the next.

Copy & Paste - quick way to copy results to a document or spreadsheet

You can highlight the tables in Stata's Results window and copy the contents. Rather than using CTRL+C, right-click on the highlighted text to get additional options:

  • Copy Text - same as CTRL+C. Not recommended for pasting tables into Excel/Word.
  • Copy Table - Aligns cells by tabs. Works well when pasting into  Excel/Word.
  • Copy Table as HTML - Copies an HTML table, which pastes well into Word.
  • Copy Table as Picture - makes a screenshot of the table. Can't edit the picture without a graphic program. Best for quickly pasting into Word.

Opening IPUMS Data in Stata

  • How to Download IPUMS Data and Open it in Stata

Help with Stata

via Email Email [email protected] with your questions!

ECON 203 Stata Cheat Sheet

  • ECON 203 Stata Cheat Sheet Cheat sheet on Stata commands for students in ECON 203.

Other Helpful Websites for Learning Stata

  • Stata Help Guides (Princeton) Includes introductory and more advanced topics, including data manipulation and statistical analysis in Stata.
  • Resources to Help You Learn & Use Stata (UCLA) Includes a 'Stata Starter Kit', helpful examples with annotated output, and a quick reference guide for choosing the appropriate statistical test.
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Basic econometrics using STATA

Profile image of MUHAMMAD ZUBAIR   CHISHTI

Stata is a computer program that allows the user to perform a wide variety of statistical analyses. In this chapter we will take a short tour of Stata to get an appreciation of what it can do.

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Stata is a statistical software package we'll be using for much of this course. 1 Stata has a number of advantages over other currently available software. For example, Stata keeps all data in memory; this makes it very, very fast. Stata is also largely command–driven (as opposed to menu–driven); while this makes its learning curve a bit steeper, once you learn Stata you will find it is substantially faster, easier, and more flexible in use than its competitors.

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econometrics stata assignment

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Features for economists

Panel data Take full advantage of the extra information that panel data provide while simultaneously handling the peculiarities of panel data. Study the time-invariant features within each panel, the relationships across panels, and how outcomes of interest change over time. Fit linear models or nonlinear models for binary, count, ordinal, censored, or survival outcomes with fixed-effects, random-effects, or population-averaged estimators. Fit dynamic models or models with endogeneity. Fit Bayesian panel-data models .

Time series Handle the statistical challenges inherent to time-series data—autocorrelations, common factors, autoregressive conditional heteroskedasticity, unit roots, cointegration, and much more. Analyze univariate time series using ARIMA, ARFIMA, Markov-switching models, ARCH and GARCH models, and unobserved-components models. Compare ARIMA or ARFIMA models using AIC, BIC, and HQIC, and select the best number of autoregressive and moving-average terms. Analyze multivariate time series using VAR, structural VAR, VEC, multivariate GARCH, dynamic-factor models, and state-space models. Compute and graph impulse responses. Test for unit roots. Perform Bayesian time-series analysis .

Cross-sectional models Fit classical linear models of the relationship between a continuous outcome, such as wage, and the determinants of wage, such as education level, age, experience, and economic sector. If your response is binary (for example, employed or unemployed), ordinal (education level), count (number of children), or censored (ticket sales in an existing venue), don't worry. Stata has maximum likelihood estimators—probit, ordered probit, Poisson, tobit, and many others—that estimate the relationship between such outcomes and their determinants. A vast array of tools is available to analyze such models. Predict outcomes and their confidence intervals. Test equality of parameters, or any linear or nonlinear combination of parameters.

Endogeneity and selection When explanatory variables are related to omitted observable variables, or when they are related to unobservable variables, or when there is selection bias, then causal relationships are confounded and parameter estimates from standard estimators produce inconsistent estimates of the true relationships. Stata can fit consistent models when there is such endogeneity or selection—whether your outcome variable is continuous, binary, count, or ordinal and whether your data are cross-sectional or panel. Stata can even combine endogenous covariates, selection, and treatment effects in the same model.

Causal inference/Treatment effects Estimate experimental-style causal effects from observational data; for instance, estimate the effect of a job training program on employment or the effect of a subsidy on production. Fit models for continuous, binary, count, fractional, and survival outcomes with binary or multivalued treatments using inverse-probability weighting (IPW), propensity-score matching, nearest-neighbor matching, regression adjustment, or doubly robust estimators. Fit models with exogenous or endogenous treatments. After estimation, test the overlap assumption and covariate balance. Add endogenous covariates and sample selection to some treatment-effects estimators. In the presence of group and time effects, you can use difference-in-differences (DID) and triple-differences (DDD) estimators. In the presence of high-dimensional covariates, you can use lasso . If causal effects are mediated through another variable, use causal mediation with mediate to disentangle direct and indirect effects.

Marginal effects and marginal means Marginal effects and marginal means let you analyze and visualize the relationships between your outcome variable and your covariates, even when that outcome is binary, count, ordinal, categorical, or censored (tobit). Estimate population-averaged marginal effects or evaluate marginal effects at interesting or representative values of the covariates. Analyze the effect of interactions. You can even trace out the marginal effect over a range of interesting covariate values or covariate interactions. You can do all of this with marginal means (sometimes called potential-outcome means), even when your “mean” is a probability of a positive outcome or a count from a Poisson model. If you have panel data and random effects, these effects are automatically integrated out to provide marginal (that is, population-averaged) effects.

Choice models Model your discrete choice data. If your outcome is, for instance, a choice to travel by bus, train, car, or airplane, you can fit a conditional logit, multinomial probit, or mixed logit model. Is your outcome instead a ranking of prefered travel methods? Fit a rank-ordered probit or rank-ordered logit model. Regardless of the model fit, you can use the margins to easily interpret the results. Estimate how much wait times at the airport affect the probability of traveling by air or even by train.

GMM GMM (generalized method of moments) can be used to fit almost any statistical model, including both exactly identified and overidentified estimation problems. Overidentified problems arise when you have endogeneity, correlation in dynamic panels, sample selection, and many other situations. With Stata, you estimate these models by simply writing your moments and enclosing the parameters in curly braces. You can easily fit cross-sectional, time-series, panel-data, or survival-data models and test your overidentifying restrictions.

Demand systems Fit demand systems to explore consumers' demand for goods and services. Given a budget and a bundle of goods and services, determine the expenditure and price elasticities for these goods. Choose between the Cobb–Douglas system, Stone's linear expenditure system, the translog indirect utility demand system, the almost ideal demand system (AIDS), the quadratic almost ideal demand system (QUAIDS), and others.

Lasso Use lasso and elastic net for model selection and prediction. And when you want to estimate effects and test coefficients for a few variables of interest, inferential methods provide estimates for these variables while using lassos to select from among a potentially large number of control variables. You can even account for endogenous covariates. Whether your goal is model selection, prediction, or inference, you can use Stata's lasso features with your continuous, binary, count, or time-to-event outcomes.

Programming Want to program your own commands to perform estimation, perform data management, or implement other new features? Stata is programmable, and thousands of Stata users have implemented and published thousands of community-contributed commands. These commands look and act just like official Stata commands and are easily installed for free over the Internet from within Stata. A unique feature of Stata's programming environment is Mata, a fast and compiled language with support for matrix types. Of course, it has all the advanced matrix operations you need. It also has access to the power of LAPACK. What's more, it has built-in solvers and optimizers to make implementing your own maximum likelihood, GMM, or other estimators easier. And you can leverage all of Stata's estimation and other features from within Mata. Many of Stata's official commands are themselves implemented in Mata.

PyStata—Python integration Interact Stata code with Python code. You can seamlessly pass data and results between Stata and Python. You can use Stata within Jupyter Notebook and other IPython environments. You can call Python libraries such as NumPy, matplotlib, Scrapy, scikit-learn, and more from Stata. You can use Stata analyses from within Python.

Forecasting Build multiequation models, and produce forecasts of levels, trends, rates, etc. Whether you have a small model with a few equations or a complete model of the economy with thousands of equations, Stata can help you build that model and produce forecasts. Your model can include both estimated relationships and known identities. You can easily create and compare forecasts under different scenarios, create static and dynamic forecasts, and even estimate stochastic confidence intervals. You can create your model by using an intuitive command syntax or by using the interactive forecasting control panel.

Survival analysis Analyze duration outcomes—outcomes measuring the time to an event such as failure or death—using Stata's specialized tools for survival analysis. Account for the complications inherent in survival data, such as sometimes not observing the event (right-, left-, and interval-censoring), individuals entering the study at differing times (delayed entry), and individuals who are not continuously observed throughout the study (gaps). You can estimate and plot the probability of survival over time. Or model survival as a function of covariates using Cox, Weibull, lognormal, and other regression models. Predict hazard ratios, mean survival time, and survival probabilities. Do you have groups of individuals in your study? Adjust for within-group correlation with a random-effects or shared-frailty model. If you have many potential covariates, use lasso cox and elasticnet cox for model selection and prediction.

Bayesian analysis Perform Bayesian econometrics analysis using one of the Markov chain Monte Carlo (MCMC) methods. You can choose from various supported models, such as panel-data, hierarchical, VAR, and DSGE models, or you can even program your own. Extensive tools are available to check convergence, including multiple chains. Compute posterior mean estimates and credible intervals for model parameters and functions of model parameters. You can perform both interval- and model-based hypothesis testing. Compare models using Bayes factors. Compute model fit using posterior predictive values. Generate predictions and forecasts. If you want to account for model uncertainty in your regression model, use Bayesian model averaging .

Survey methods Whether your data require a simple weighted adjustment because of differential sampling rates or you have data from a complex multistage survey, Stata's survey features can provide you with correct standard errors and confidence intervals for your inferences. Simply specify the relevant characteristics of your sampling design, such as sampling weights (including weights at multiple stages), clustering (at one, two, or more stages), stratification, and poststratification. After that, most of Stata's estimation commands can adjust their estimates to correct for your sampling design.

Meta-analysis Combine results of multiple studies to estimate an overall effect. Use forest plots to visualize results. Use subgroup analysis and meta-regression to explore study heterogeneity. Use funnel plots and formal tests to explore publication bias and small-study effects. Use trim-and-fill analysis to assess the impact of publication bias on results. Perform cumulative and leave-one-out meta-analysis. Perform univariate, multilevel, and multivariate meta-analysis. Use the meta suite, or let the Control Panel interface guide you through your entire meta-analysis.

Automated reporting and customizable tables Stata is designed for reproducible research, including the ability to create dynamic documents incorporating your analysis results. Create Word or PDF files, populate Excel worksheets with results and format them to your liking, and mix Markdown, HTML, Stata results, and Stata graphs, all from within Stata. Create tables that compare regression results or summary statistics , use default styles or apply your own, and export your tables to Word, PDF, HTML, LaTeX, Excel, or Markdown and include them in your reports.

Over many years, Stata has been the one constant in a perpetually changing software toolbox. For me, it remains the fastest and most thorough tool for fully understanding a complex dataset. Plus it’s the easiest tool to extend and customize. I can’t imagine working without it.

— Sean Becketti Financial industry veteran with three decades of experience in academics, government, and private industry

Check out Stata's full list of features , or see what's new in Stata 18 .

Intuitive and easy to use . Once you learn the syntax of one estimator, graphics command, or data management tool, you will effortlessly understand the rest.

Accuracy and reliability. Stata is extensively and continually tested. Stata's tests produce approximately 5.8 million lines of output. Each of those lines is compared against known-to-be-accurate results across editions of Stata and every operating system Stata supports to ensure accuracy and reproducibility.

One package. No modules. When you buy Stata, you obtain everything for your statistical, graphical, and data analysis needs. You do not need to buy separate modules or import your data to specialized software.

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econometrics stata assignment

How To Get The Grades You Need For Econometrics With STATA Help

STATA is an analytical tool that is used in the computation and presentation of the complex data in order to make it simple for anyone to interpret. When using this software application, you have to know how to go about it in the case you want to solve a statistical problem. Most students who use this tool for the first time will not know where to start. In order, to get the grades you want for college acceptance, you have to seek STATA assignment help to make your work easier. The good thing about what we offer at economicshelpdesk.com is that, we have a pool of qualified tutors who have a deep understanding of multiple statistical software applications. They thus offer quality STATA assignment online help without much hustle.

Highlight Your Objectives

You have to know what you want to attain at the end of it all. In this case, it is that college acceptance. If you want to pursue statistics and use STATA to analyze complex data, then you have to well in that subject matter. With our exceptional STATA help online services, you will be good to go. We offer end to end solutions for all topics that are giving you a headache that relate to STATA homework projects.

Get the Right Help from the Right Tutor

It is not easy to trust just about anyone without looking into their profile and reviews. You have to do your homework before you trust them to provide the STATA homework help you are looking for. With a trusted and most reliable site like what we have with economicshelpdesk.com, you are bound to find the best STATA assignment online tutors we have at your disposal.

Submit Your Assignments Early

The earlier the better when it comes to getting help with STATA homework. This will give you the time to go through the project once it is done and understand the topic in depth. As a result, you will be able to tackle any other problem of similar nature that comes your way. However, when you submit it late, you might not have the luxury to go through it before you hand it over to your professor.

Practice Makes Perfect

It is not just about getting STATA help and going through the assignment, you have to do your part. You will need to practice the things that our tutors have indicated in details after the assignment is complete. With our STATA assignment help, you will receive all the learning materials you need to score better grades in school for college acceptance.

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09-Feb-2018 09:45:24    |    Written by admin

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Econometrics Homework Help: How Does It Work?

Econometrics Homework Help

We know that students often need econometrics homework help. But how does one go about getting help? How does it work?

One of the most important things you need to do when getting econometrics help is to make sure that you understand what’s going on. A student first to understand both what they need to do, like data cleaning, for instance, or regression analytics. But they also need to understand how to do these things. As such, they need to have a firm grasp of STATA, the software they’ll be using when tackling their assignment. This is where econometrics help comes in.

Updated: 1 May 2023

STATA Assignment ‘s econometrics homework help assists students in several ways. First, it gives students detailed explanations of each do. file STATA code. This ensures that students firmly grasp what the codes are and what they do. Next, STATA Assignment has students do code replication. In other words, students come to properly understand each command that they’re using, as they’re using them. This way, students learn by doing and replicating, and commit what they’re doing to memory. In a sense, the work they’re doing even becomes like muscle-memory. Because of this, students are able to ace their STATA quizzes and assignments without any trouble.

STATA Assignment also helps students with data cleaning – the process of eliminating or fixing incorrect, incorrectly formatting or missing data. Our company helps speed up this process, which can be otherwise tedious. Thus, students are able to pick up speed without making any mistakes and work off of accurate data to test hypotheses and conduct analyses. Thanks to this, students turn in accurate and detailed reports for their courses, get higher grades and naturally end up with a higher GPAs. By the time graduation rolls around, students moved into their chosen career paths confident in their mastery of STATA- a very useful skill in a highly technologically driven world!

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  4. Why Choose STATA for Econometrics Assignments?

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  1. Econometrics I assignment

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COMMENTS

  1. Homework 2

    Assignments Homework 2 Solve one of problems 1, 2, or 3 from Lecture 2 (PDF) and one of problems 4 or 5 from Lecture 2. You can use any econometric/statistical software you like. The data sets are posted below.

  2. Sample Exams Econometrics Stata

    Sample exam 1: Econometrics, general exam a. Consider the multiple regression model with two independent variables. We have a random sample of N observations. The regression equation is YX 01122 X for which we assume that the error term is independent of the explanatory variables X 1 and X 2.

  3. Econometrics Application

    Students are expected to analyze the dataset using STATA or their statistical software of choice (STATA commands will be used in lecture) and write a short paper explaining their findings from the provided dataset (s), using guiding questions. Exams can be considered an extended assignment as they cover more than one econometric model.

  4. ECO 351 HW1 Fall 22

    ECO 351 Introduction to Econometrics Assignment 1 Due Date: November 17, 2022 There are 4 questions in this assignment. You are asked to answer all questions. You can receive a maximum of 100 points for this assignment.

  5. C.Cameron: Analysis of Economics Data 102

    The most common form of academic misconduct in Economics 102 is copying from past assignment solutions or copying (close to exact or exact) from other students. The most common penalty for doing so (in addition to reporting to SSJA) will be to receive zero for that assignment and additionally having your course grade reduced by one grade ...

  6. PDF Economics 4848 Applied Econometrics Fall 2022

    Stata Practice Assignments (5% total): One assignment is due the week before each exam. These will be completed on Canvas. Each has a 10% grade penalty each day if submitted late, and they will not be accepted once the assignment closes and the answers are posted.

  7. STATA Resources

    Library Resources to Connect Econometrics with Stata code. Learn About Simple Regression in Stata With Data From the Consolidated State Performance Report (2012-2013) ... This assignment by use of a population threshold introduces a discontinuity that splits practically identical municipalities into two groups, one group with a proportional ...

  8. An Introduction to Modern Econometrics Using Stata

    An Introduction to Modern Econometrics Using Stata can serve as a supplementary text in both undergraduate- and graduate-level econometrics courses, and the book's examples will help students quickly become proficient in Stata. The book is also useful to economists and businesspeople wanting to learn Stata by using practical examples.

  9. PDF An Introduction to Modern Econometrics Using Stata

    A Getting the data into Stata 277 A.1 Inputting data from ASCII text files and spreadsheets 277 A.I.I Handling text files 278 Free format versus fixed format 278 The insheet command 280 A.I.2 Accessing data stored in spreadsheets 281 A.1.3 Fixed-format data files 281 A.2 Importing data from other package formats 286 Β The basics of Stata ...

  10. Library Research Guides: ECON 203: Econometrics: Use Stata

    To start a new log: First change your working directory to the correct folder (cd command). Then in the command box type log using "logname", text. Give your log file a usefulname such as 'Lab2Feb6.log.'. Begin a new log file each time you begin working in Stata or use the append option to add on to an existing log file.

  11. ECONOMETRICS with STATA. Examples and Exercises Solutions Manual

    Author: Maria Perez 0 solutions Frequently asked questions What are Chegg Study step-by-step ECONOMETRICS with STATA. Examples and Exercises Solutions Manuals? Why is Chegg Study better than downloaded ECONOMETRICS with STATA. Examples and Exercises PDF solution manuals? How is Chegg Study better than a printed ECONOMETRICS with STATA.

  12. Basic econometrics using STATA

    For example, Stata keeps all data in memory; this makes it very, very fast. Stata is also largely command-driven (as opposed to menu-driven); while this makes its learning curve a bit steeper, once you learn Stata you will find it is substantially faster, easier, and more flexible in use than its competitors.

  13. PDF Econometrics using STATA

    Goal : make a 1-page critical review of the paper/chapter brief summary of the paper (topic, method, main points, results) discuss method, experimental design, interpretations, conclusions relate it to the class criticisms, shortcomings ? ... bonus based on quality/clarity/concision

  14. PDF Introduction to STATA with Econometrics in Mind

    Introduction to Stata with Econometrics in Mind John C. Frain. February 2010 Abstract This paper is an introduction to Stata with econometrics in mind. One aim of the proposed methodology is the keeping of appropriate records so that results can be easily replicated. These records should meet the requirements of management and internal

  15. ECNS 562: Econometrics 2

    STATA Resources Introductory Resources. My Stata Notes ... Homework Assignments WOOLDRIDGE Data for homework ... Department of Agricultural Economics and Economics Montana State University P.O. Box 172920 Bozeman, MT 59717-2920. Tel: (406) 994-5634

  16. Economics

    Economists have relied on Stata for over 30 years because of its breadth, accuracy, extensibility, and reproducibility. Whether you are researching school selection, minimum wage, GDP, or stock trends, Stata provides all the statistics, graphics, and data management tools needed to pursue a broad range of economic questions. Features for economists

  17. Econometrics Stata Assignment Quick Guidance : r/econhw

    This assignment aims to build an economic growth model and discuss the policy implications arising from this model. The assignment is: a) Read the following articles on economic growth econometrics: Mankiw, N.G., Romer, D., and Weil, D.N. (1992). A Contribution to the empirics of economic growth.

  18. Assignment for Econometrics

    2 =thedisposable (i.,after-tax)income ($,inbillions) X 2 =theprimerate (%)charged bybanks a. Whatisthemarginalpropensitytoconsume (MPC) -theamountofadditional consumptionexpenditurefromanadditionaldollar'spersonal disposable income? Answer: - What is the marginal propensity to consume (MPC) From our given model the MPC is the coefficient of X

  19. Econometrics Assignment 2 Stata

    Econometrics - Assignment 2 Econometrics (BPRA203)Assignment Cross-National Analysis and Introduction to StatThe dataset "Introduction Stata 2020" on Brightspafor at least 72 countries:We constructed a model which tries to explain the variableinequality.

  20. STATA for Econometrics assignment tutors

    1 STATA for Econometrics STATA Applied Econometrics using STATA Data Analytics Services: Full semester support, online teaching, assignments, quizzes, and exams help with thesis and reports. I will be your Research Assistant. ⭐⭐⭐⭐⭐Solutions + one-on-one Zoom class for an explanation.

  21. Econometrics Help for STATA

    Our goal is to provide quick online STATA Econometrics help to students by providing detailed in-depth explanations of each do. file STATA code. Based on feedback from students, this is the best way to learn STATA - a combination of 'learning by doing' and 'code replication' methods.

  22. How To Get The Grades You Need For Econometrics With STATA Help

    In order, to get the grades you want for college acceptance, you have to seek STATA assignment help to make your work easier. The good thing about what we offer at economicshelpdesk.com is that, we have a pool of qualified tutors who have a deep understanding of multiple statistical software applications.

  23. Econometrics Homework Help: How Does It Work?

    STATA Assignment 's econometrics homework help assists students in several ways. First, it gives students detailed explanations of each do. file STATA code. This ensures that students firmly grasp what the codes are and what they do. Next, STATA Assignment has students do code replication.