Questions tagged [regression]

In statistics, regression analysis is a statistical process for estimating the relationships among variables. It includes many techniques for modeling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables (or 'predictors').

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Interpreting regressions results: different scales and variables interaction

I want kindly ask if someone can help me interpreting the results of regression that I need for my master thesis. The model is this : countries are indexed by i and time by t. Dependent variable ...
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Should a Price Elasticity of Demand model exclude items that sold out or marked down from the original price

Consider a Price Elasticity of Demand model built with linear regression to estimate the Percent Change in Quantity Demanded given a Percent Change in Price specifically for specialty items which have ...
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How to determine correct fixed effects in linear regression model using unbalanced paneldata

I am currently working on a research project regarding the introduction of mandatory earnings guidance regulation in multiple countries within a time span of 10 years (staggered adoption). As I can ...
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Should coefficient on interaction term be positive or negative?

I have the following model for housing prices price = $\beta_0$ + $\beta_1$ sqrft + $\beta_2$ bedrooms + $\beta_3$ sqrft $\times$ bedrooms + $\beta_4$ bathroom, where sqrft is square feet. I am ...
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Possible regression biases with GDP [x] vs Health expenditure [y] (both per capita)

I am regressing per capita health expenditure on per capita GDP. I have 3 data columns (health expenditure, gdp, population) So my regression function is healthexpenditure/population = b0 + b1.(gdp/...
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Generating Variable frequency

I three variables, zipcode, date (month_year) and name of an installer. I need to generate: 1- a new var that is equal to the number of repetitions the installer name is repeated in month_year and in ...
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654 views

What is a good proxy for government quality?

Is it ok to use corruption as a proxy for government quality?
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When using OLS is it always necessary to drop the weak and insignificant variable? [closed]

Some of my variable shows weak collinear relationship on my dependent variable.. how should I address this?
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Can a complex interaction term mean more than what it's composed of?

I'm cross-posting this question on both Economics and Cross Validated to get answers from a different perspective on each field. It is generally accepted to cross-post if the question is tailored to ...
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How should I rebase my GDP?

I have a constant GDP data from 1988 to 2009 in constant 1985 prices and GDP data from 2009 to 2017 in constant 2000 prices. My question is how should I rebase my GDP? Upon searching the web, i don'...
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What is the tolerable level for multicollinearity? and possible remedial measures for it?

My data has issues of multicollinearity. Upon estimating, I found out that my data have high levels of VIF In however I was confused as to what level of VIF can I possibly ignore the issue of ...
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Transformation of cutpoints in Ordinal Probit/Logit regression

The likelihood for an ordinal probit/logit regression model is given as - $f(y|\beta ,\gamma ,z ) = \prod_{1}^{n} \left [ \Phi (\gamma _{j} - x_{i}'\beta ) - \Phi (\gamma _{j-1} - x_{i}'\beta ) \...
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How do I fill gaps in my data?

In my study, I have 5 independent variables which contains 21 observation each. However one of my independent variables have 3 gaps. What should I do? e,g I would need to know the effect of ...
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Are unit root tests necessary or useful on small samples of time series data?

I have a 16 year time series (annual frequency with 16 observations). I will conduct an OLS regression. In this setting do I need a unit root test? Do you have additional suggestions for things that ...
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Should the control variables in an econometric regression be correlated with both the dependent and the primary independent variables?

If, for instance, my dependent variable is some happiness index, and my independent variable is a dummy for whether they experienced some randomly occurred natural disaster. I am trying to analyze the ...
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1answer
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Correct Equation for Pooled OLS Regression (with Time Dummies and Interaction Terms)

I have a question regarding a pooled OLS regression. Basically, I’m not sure I’m writing out the equation properly. The data is on feature films released between 2006 and 2016 (11 years); box office ...
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What's the use of '% to GDP' type of variables?

In my study I will look for the relationship between the Gini coefficient and trade, FDI and other variables. However, as I was regressing it... the result turn out to be insignificant. My data that I ...
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How do we calculate Beta in a OLS regression of the mean of y on the mean of lag of y?

In a simple OLS regression we calculate the estimator Beta by dividing the covariance of x and y by the variance of x. How do we calculate the estimator Beta if we regress the mean of a variable (at ...
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What R-squared is a low R-squared?

I keep hearing that R-squared does not really matter in economics research and that due to the unpredictable human nature, economics research regressions tend to have low R-squared. But how much is ...
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OLS estimator derivation: second-order condition to prove global minimum?

In deriving our ordinary least squares estimates, we can partially differentiate the sum of squared errors $\sum_{i=1}^{n} {e_i^2} = \sum_{i=1}^{n} {(Y_i- \hat{\alpha}-\hat{\beta}X_i )^2}$ with ...
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1answer
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Multivariate linear regression: how to test for whether the slopes are the same?

If I regress wages on education and the dummy variable gender using a linear conditional expectation function (wage = a + b(education) + c(gender)), how can I test that the slope b is the same for ...
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Estimation of investment adjustment costs

Hi I am working on a problem set in my macroeconomics course. I have a hard time figuring out how to get started on one of the problems. The set-up is the following. A price-taking firm maximizes: $\...
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How to do elasticity modeling for products where there is slab pricing like electricity?

I have few product categories eg prod1 prod2. Each category have similar products. So prod1 has 3 similar products with slight difference in features and prod2 has 5 products with slight differences. ...
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Demand equation with demographics

I am trying to reconcile the derivation of a demand equation with what I actually run in an OLS model. After solving $$max_{x_1,x_2}U(x_1,x_2)= \alpha ln(x_1) + \beta ln(x_2)$$ subject to $$p_1x_1+...
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2answers
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Unbiased but inconsistent estimator [closed]

Assume a random sample X1, ..., Xn with a normal distribution with mean μ and variance σ2. How do we know the following estimator is unbiased, but inconsistent?
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Justification for my Random Effects estimation

I need to defend my use of the Random Effects (RE) estimator in my economics project. I've been told in cross validated that the proper place for the question is here. The causal effect of the ...
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Controlling for a variable in OLS - Stratification and Reaggregation. Simple Example

In his engrossing book "Naked Statistics" Charles Wheelan begins to explain how controlling for variables works by stratifying the sample. However, he stops short of explaining the reaggregation, ...
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Profit maximization problem using linear regression (pooled OLS)

I'm currently on a university assignment where I'm stuck more or less in the middle. I have to answer the following problem: Suppose you are interested in estimating the production function for ...
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How do I measure effects over years in panel data with individuals?

I'm working with a longitudinal panel dataset that surveys the same few thousand individuals biennially and I have six years of this data. My dependent variable would be how much individuals spend on ...
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Can A/B be a better variable than separate A, B in linear regression?

While learning Econometrics, I got curious to know whether A/B can make a better variable than separate A and ...
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1answer
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Linear Regression Assumptions of Homoskedasticity

When I studied linear regression analysis, one of the assumptions taught was that of homoskedatiscity. I understood that homoskedasticity was required for significance testing on the coefficients. ...
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1answer
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Why does instrument exogeneity imply conditional mean zero?

In the following slide ECON4150 - Introductory Econometrics Lecture 16: Instrumental variables, Monique de Haan it says that "instrument exogeneity implies $E[u_i \mid Z_i]=0$" where instrument ...
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1answer
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Dummy variable regressor OLS coefficient formula

Consider the standard linear regression model: $y_i = \alpha + \beta D_i + e_i$ where the coefficients are defined by linear projections and $D_i$ is a dummy variable. In the population, the ...
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When is an OLS parameter unchanged on a subsample?

There is a sample of $n$ observations, each element has a numeric $Y$ and $X$ characteristic. There is an OLS regression over the sample $$ Y = b_0 + b_1 X + \textbf{u}, $$ $\textbf{u}$ being the ...
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Regression on derived consumer preference

I have a data set with some demographics of consumers who bought a product that can be used to imply their preference (beta) using Cobb-Douglas (see comments of original question). I’d like to check ...
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1answer
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Is there any specific distribution that is recommended for modelling individual income?

I'm a statistician and my colleagues work with income data every now and then, but they usually apply some arbitrary cut-off and go with logistic regression. I know there's an infinite range of ...
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Does the linear probability model require the regressand to be zero/one-valued?

Typically, the dependent variable in a linear probability model (LPM) is a 0/1-valued binary variable. What if the dependent variable $y_i$ is still binary but take on general values $a$ and $b$ ...
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1answer
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Subset of Data in a gravity model

In my last subject of studies I am analyzing trade costs in a gravity model, e.g. multilateral trade resistance and bilateral trade resistance terms. The gravity model assumes world trade. However, I ...
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Confounding versus endogenous variables. What is their relative hierarchical position?

There are valuable resources on the lexicon of types of variables quickly accessible, such as here. However, some of these concepts appear side-by-side often enough to make them confusing. For ...
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Indicator variables over unequal periods?

I'm comparing the volatility of capital flows using a panel data regression. I would like to examine changes in volatility over different periods (e.g. before financial crisis, financial crisis, ...
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Multiple regression

How can I test in a multiple regression model whether a drop of 1% in $x_1$ will cause a larger effect than a 1% drop in $x_2$, given that I used the growth rates of my dependent and independent ...
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2answers
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conditional mean and conditional median

In Wooldridge's book (Page 452), it says When linear absolute deviation (LAD) methods are applied alongside OLS, thre are often reasons to think a priori that OLS and LAD will not produce similar ...
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Controlling for interaction effects

In a recent paper, Edelman et al. examine (amongst other things) how discrimination on AirBnB varies with the characteristics of hosts. First, they conduct a field experiment which involves sending a ...
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1answer
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Constant Regressor in GLS

Consider the following regression model: $y_{i1}=\beta_1 +u_{i1}$ $y_{i2}=\beta_{21}+\beta_{22}x_i+u_{i2}$. If $E(x_i' u_{i1})\neq 0$ and $E(x_i' u_{i2})=0$, will we get consistent estimators ...
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Categorical variable as explanatory variable (right hand side)

In a linear probability model, or any sort of regression, one can use fixed effect estimation by simply adding in a STATA code i.something. This "something" can be either a village, a county or a ...
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1answer
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How to get the effect of one dummy variable against many others?

I have the following regression: wage = constant + (beta1)*michigan+ (beta2)*california+...+(beta49)florida+(beta50)education + u where michigan is equal to one if the person is from michigan and ...
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Econometrics - Simultaneous Equations and Perfect Inelasticity in the Context of Regression

Assume a certain market can be described by Demand Function: $$Q_{d, t} = \alpha_0 + \alpha_1 P_t + \mu_{1, t}$$ Supply Function: $$Q_{s, t} = \beta_0 P_t + \mu_{2, t}$$ The price in this market is ...
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3answers
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Sample used in calculating the sample regression function

Does the OLS (ordinary least squares) method of regression consider only one sample value in calculating the sample regression function (SRF)? If not, then how is the SRF created when there is more ...
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Does endogeneity matter when neither independent variable nor error term are correlated with dependent variable?

if the double arrows show that X and the error term are correlated, but that neither variable affects Y, is endogeneity a problem in this scenario? Why or why not?
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Proving consistency of quantile regression estimators

I have asked the question on the statistic section on stack exchange, but no one was able to give me an answer. I think this is actually is a question that touches econometrics so I am going to ask it ...