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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How to estimate a system of equations with missing values in dependent variable with sureg?

I am trying to estimate vote shares of different parties. So, suppose I have 4 parties, each having its own column in the data set. Hence, the sum would be tending to 1. Now, if a party does not ...
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How to recognize correlation in spurious regression case

Assume we are given two independent random walks $$ Y_t = Y_{t-1} + \varepsilon_{1, t}, \quad \varepsilon_{1, t} \sim \mathcal{N}(0, 1) \\ X_t = X_{t-1} + \varepsilon_{2, t}, \quad \varepsilon_{2, t} \...
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How to estimate an SUR model in R with fixed effects and clustered standard errors?

I want to estimate an SUR (Seemingly Unrelated Regressions) model. I tried using systemfit and its wrapper Zelig. But I am not ...
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What should we do if the subsample have the opposite results to the general results?

In my replication study, I examine whether a law (a law implemented staggered by different countries) has an impact on firms' cash equivalents. The result turning out for the whole sample is that the ...
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Intercept in 2nd-stage Error Correction Model (ECM) regression — yes or no?

When doing a two-step ECM regression, do we add an intercept in the 2nd stage regression? I've seen course notes that add an intercept in the ECM, but some do not, so I'm confused if I should include ...
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Event study by Kleven

I was reading the following paper by Henrik Kleven et al. https://www.henrikkleven.com/uploads/3/7/3/1/37310663/kleven-landais-sogaard_nber-w24219_jan2018.pdf The estimate the child penalty on wage ...
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How to interpret fixed effects from a binary logit model in which all dependent variables are categorical? Marginal effects does not work

The study is on survey data from UK households with a lot of missing variables. I ran a logit regression to predict the probability of Y (binary variable)and estimated the corresponding marginal ...
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Interpretation of coefficients in a regression with a lagged dependent variable

I have estimated the following dynamic panel data model using GMM:           $\ln Y_{it}=\beta_0+\beta_1\ln Y_{it-1}+\beta_2\ln X_{it-1}+\epsilon_{it} $ where $Y$ is employment and $X$ is productivity....
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40 views

Suggested model for dependent variable of different groups

I want to test the impact of X on Y. The dependent variable Y is being employed. Now, I want to see if the impact of X is different for those employed in agriculture (A) and non-agriculture (N) ...
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90 views

Why we need to control for the interation of year and industry fixed effects?

Normally, we control for firm and year fixed effects, but in some case I saw people control for the firm along with yearxindustry or firm and yearxregion fixed effects. Could you please hint me why ...
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Is exogeneity guaranteed for a lottery-generated instrumental variable?

If using $z$ as an instrument for $x$, to study the effect $x$ has on $y$ and given that $z$ was indeed generated through a lottery, is it definite that exogeneity of $z$ will hold? I have looked at ...
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Predicting covariates into “observed” and “unobserved” part

I recently saw a paper where they run a regression of the covariate of interest $X_{1}$ on the outcome $Y\in\{0,1\}$ without further controls $$ Y = \alpha_{1} + \beta_{1} X_{1} + \epsilon_{1} \tag{1}...
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Joint significance test in a difference-in-differences setting

I ran the following difference-in-differences regression in software and have some questions about the interpretation of the resulting coefficients and their (joint) significance: $$ P_{it} = \gamma_i ...
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How should I regress income inequality on economic growth?

I would like to know which variables to use to regress income inequality on economic growth. For income inequality, I am thinking of using the Gini index, but don't know what measurement exactly. For ...
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Question about using elasticities to compare difference rates but with different normalization

Lets say I am estimating a regression of a death rate per 100k people on an economic shock, so: $y = \beta_o + \beta_1 * X+ error$ where the dependent variable is the death rate, and x is the measure ...
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How to interpret fixed effects?

I want to interpret the output of a fixed effects regression and need help with interpreting the country-fixed effects. The regression is the following: ...
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How to explain negative correlation between quantity sold and expenditure on advertisement?

I have received the following dataset from our economics Professor. It has 15 observations and 4 variables - 'qsold' (quantity sold of product X), psn (price of X), ...
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Does random sampling cause zero conditional mean?

In the lecture notes of my development economics class, it says that " In the regression model : Yi = β0 + β1Xi + ui, if Xi is randomly assigned, then Xi is independent of ui, i.e., E(ui|Xi) = 0, ...
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66 views

Why is it assumed that covariance equal to $0$ or independence between $y$'s in the simple linear regression model?

I have started a book of econometrics and in the first pages are stated the assumption used in the linear regression model, which are : The third one is the one I don't understand, why it has to be ...
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Regressing (Very) Smooth Time Series

What are the possible problems/issues of regressing smooth time series with almost no fluctuation? Here is a specific example. Is there anything I have to pay attention to when interpreting ...
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Is this an an endogeneity/simultaneity problem?

I would like to know if the logic in these two situations is correct. Situation 1: Let's say we have a continuous dependent variable, $y_1$, that then has a causal impact on an unobserved variable, $\...
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Is this an endogeneity problem?

Let's say we want to determine the impact of $y_2$ on $y_1$, which are related as follows: $$y_1 = f(y_2, x_1,e)$$ where $$e = g(y_3,x_2, u_1), \space y_2 = h(y_4,x_3, u_2), \space y_3 = m(y_4, x_4,...
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Verification of logic behind instrumental variable approach

I would like to know whether the following reasoning regarding the instrumental variable approach is acceptable. I understand there are case-by-case factors that affect the applicability of ...
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What's the minimum number of datapoints in order to run a diff-in-diff?

I was thinking about running a diff-in-diff with fixed effect in order to deal with a panel data experiment. The problem is that I don't know how many datapoints I need in order to the experiment be ...
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Choice between dummy variables and Likert scale in Linear Regression

I want to run a linear regression based on the data gathered using a questionnaire. Several of the questions have the following form: How much do you spend on xyz in a month? a. Less than \$50 b. \$50 ...
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1answer
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Making sure the p-values of my OLS estimates are correct

I have learned the basics of the Classical Linear Regression Model and also various diagnostic tests to check if the assumptions of the CLRM are met, such as homoskedadticity, absence of near perfect ...
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Why don't economists do regression diagnostics?

There is a lot of talk about regression diagnostics in tutorials on the web, but then in economics research papers nobody actually reports residual plots, collinearity checks etc. Is there any reason ...
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113 views

Arellano and Bond (1991) GMM estimation in R by using plm package

I am a last-year student at university, currently working on my Bachelor's (so still learning R), and I really hope that you would suggest a potential solution (even if to use Python). So, the main ...
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Questions regarding ordered probit model

I am currently working on a hypothetical research proposal for a course at my university. I am using data from three Afrobarometer surveys conducted in 34 African countries in the years 2011-2013, ...
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How do I work with the growth accounting framework in a regression?

I am currently writing my master's thesis with the topic "The impact of digitalization on economic growth in China and Germany". My idea is to take a technology such as Industry 4.0, IoT or ...
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Diff-in-Diff framework where treatment time is not fixed and multiple treatment group with sub level of treatment

The study is analyze a data for 30 yrs time period with two treatment group denoted T_1 & T_2 and a control group. Treatment ...
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How to calculate semi elasticity in fixed effect model with interaction

Given the model specification $$Y_{it} = \beta_1 X_{it} + \beta_2 D*X_{it} + FE_{i} + e_{it}$$ The above model specification is a Fixed effect model with interaction term ($X_{it}$ interacting with D- ...
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Regression based on the Solow Model

If we have the following regression based on the Solow model: log(yi) = β0 + β1 * log(si) + β2 * log(ni + gi + δi ) + ei And we know that based on: y* = 〖(s/(n + δ + g))〗^(α/(1-α)) log(y*) = α/(1-α) * ...
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1answer
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The instrument in “The Colonial Origins of Comparative Development”

I am hoping to understand when an instrument is appropriate. For the purposes of this question, I'm considering a simplied version of the model in AJR (2000): $$\begin{aligned}\text{GDP} &\sim \...
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Which values to assign to a quantified dummy variable

I am working on a data set from kaggle (https://www.kaggle.com/spscientist/students-performance-in-exams) about how student performance relates to some explanatory variables, such as if the school ...
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How to find $\phi$, that denotes the correlation of signals among informed traders?

Since I do not have an answer on Quantitative Finance in my question I cross-post here the problem to tag some other categories The following assumptions are part of the paper of Back, Chao and ...
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Log-Linear Model

I know that the log-linear model shows the percent change in y if there is a one-unit change in x but how would you solve for it the other way to show a percent change in x if there is a one-unit ...
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247 views

R's felm() fixed effects vs. factor() within lm()

I am wondering why using felm's fixed effect option versus using the factor() function is different? I was under the impression they were one in the same? I am running a panel regression where i is ...
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1answer
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Difference in interpretation of log-lin coefficients with binary variable

Consider the model: $$y_i=\beta_0+\beta_1D_1+\beta_2D_2+u_i$$ Where $D_1=\{0,1\}$ and $D_2=\{0,1\}$ are binary (dummy) variables, and $y_i$ is a continuos variable in levels. In this model, for ...
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graph of dependent variable after years of restructuring in panel data

i'm not very able to use stata. For my thesis, I have a panel data(1970-2017) for different countries and a lot of variables. In this dataset, there is a dummy (dhairendH) that is equal to one in the ...
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1answer
80 views

Age effect when controling for individual fixed effects and time fixed effects

I have a individual-by-year panel. Although age is varying within an individual, its variation is fully absorbed when I include individual fixed effects and time fixed effects. This is because each ...
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1answer
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Logit/Probit with numbers different than 0 or 1?

I am trying to find an econometric model that helps me to answer the following. I would like to measure how much the increase in the cost of a production factor (my X) shifts the supply curve of a ...
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Is this weighted least squares or just weighting the dependent variable

I am a little confused as to what the following line means. Do the authors mean they run a weighted least squares using the sample size as weights, or just weight the dependent variable using the ...
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3answers
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Why would regression coefficients be different on a subsample?

If I'm running a linear regression for example, and I take out some points, wouldn't the same line/plane still fit the data? If not, wouldn't that show that the data doesn't have a linear relationship?...
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1answer
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How to design / interpret a difference in differences regression [closed]

I have a set of active scientists and editors. I want to study the effect that becoming an editor has on the different outcomes of a scientist (such as citation count and publication rate). I decided ...
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Obtain the OLS estimators of the simple model from the multiple model

I'm looking for the answer to this question: In the context of the simple regression model (two variables) we know that the estimators of OLS are given from: $\hat{\beta}_{1}=\frac{Cov(x_i.y_i)}{Var(...
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1answer
183 views

Calculating natural rate of unemployment

I have sample data on unemployment rate in a market and am looking to calculate the natural unemployment rate. The natural unemployment rate I obtained is constant over a time period, which is not a ...
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Non Linear regression to obtain diminishing marginal effect / elasticity

I am working with some real estate data on housing units. For a given market, I have data on occupied units, rents, and control variables such as population, demographics, income levels etc. I'd like ...
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Question on estimating elasticity and cross elasticity with log-log regression model

For a regression model: Y = B0 + B1.X + B2.X2 + U, B1 and B2 is the marginal effect on ...
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Compute the inverse of a conditional quantile regression output

Short Clarification : This question was asked at the Cross Validated SE (Question at CV) but one highlighted in the comments, that this might be more applicable to this SE due to its economic topic. ...

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