The Stack Overflow podcast is back! Listen to an interview with our new CEO.

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').

Filter by
Sorted by
Tagged with
13
votes
5answers
10k views

What happens if the “control variables” are also endogenous?

I work in Political Economy, and a lot of the models include "innocent" control variables such as population, inequality, colonial legacy, etc. so that the author can claim unbiasedness on their ...
9
votes
2answers
470 views

Regression over the whole population

What's the meaning of the standard error of a coefficient in a regression when the whole population is included? I've been so puzzled by this question. Because it seems to me, standard errors make no ...
8
votes
1answer
308 views

Alternative way of deriving OLS coefficients

In another question of mine, an answerer used the following derivation of OLS coefficient: We have a model: $$ Y = X_1 \beta + X_2 \beta_2 + Z \gamma + \varepsilon, $$ where $Z$ is unobserved. Then ...
7
votes
2answers
12k views

Outputting Regressions as Table in Python (similar to outreg in stata)?

Anyone know of a way to get multiple regression outputs (not multivariate regression, literally multiple regressions) in a table indicating which different independent variables were used and what the ...
7
votes
1answer
148 views

Literature on factors affecting number of houses built

Is there any existing literature on the various factors affecting the number of houses constructed in a particular city over, say, a given month? Factors might include: quality of housing stock, a ...
6
votes
3answers
123 views

More complex than simple and multiple regressions?

I am currently in an Econometrics class that requires us to write a research paper that showcases our skills in regression/ modeling. What is slightly more complex than simple and multiple ...
6
votes
3answers
5k views

Robust Standard Errors in Fixed Effects Model (using Stata)

I'm trying to figure out the commands necessary to replicate the following table in Stata. This table is taken from Chapter 11, p. 357 of Econometric Analysis of Cross Section and Panel Data, Second ...
6
votes
1answer
4k views

How do I calculate price elasticity of demand using historical price and quantity data?

I work for a company that produces retail items and I am tasked with calculating the price elasticity of demand for a subcategory that shall remain unnamed. I have 5 years of monthly market data that ...
6
votes
1answer
157 views

How to specify a Diff-In-Diff Regression with multiple time periods?

I'm working on analysing experimental data for a thesis project. The data consists of subjects performing the same task over five rounds, and I'm interested in the difference in trends between ...
5
votes
2answers
285 views

Proof coefficient in log-log model is equal to coefficient of elasticity

I am trying to see how we treat $\varepsilon$ in the following proof: Suppose we have a log-log single variable regression model $$ \ln(y) = \alpha + \beta \ln(x) + \varepsilon $$ then take partial ...
5
votes
2answers
525 views

Estimating price elasticity of demand

I have 25 quarterly observations and I want to estimate price elasticity of demand. I intented to use GMM-IV estimator. However, I read that it is not good for small samples. What can you suggest me? ...
4
votes
4answers
2k views

Alternative to linear regression

I'm third year economics student and all econometrics we had so far and basically all empirical studies in economic subjects we had so far are linear regression. Is there any alternative, can anyone ...
4
votes
2answers
574 views

Including (demand) price elasticity in a price regression model

I am wondering how to include price elasticity (demand side) in a linear price regression model that is based on asuming price is the result of demand=supply. Constructing a price regression under ...
4
votes
1answer
183 views

Is a hedonic regression a reduced-form?

If house prices are a function of location, physical characteristics and an error term i.e. house_price = f (location, physical, e) And I estimate a regression with the log of house price as my ...
4
votes
1answer
50 views

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 ...
4
votes
2answers
336 views

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 ...
4
votes
3answers
88 views

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?
4
votes
1answer
356 views

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 ...
4
votes
1answer
44 views

Longitudinal microdata on house migration patterns

I am looking for a database that has longitudinal microdata for housing migration patterns. Optimistically, the data would look something like: In 2006, Person #2341 made $X, was Y years old, and ...
4
votes
1answer
69 views

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 ...
4
votes
0answers
230 views

Explanation of paper's econometric assumptions

The authors of this paper (http://andrewleigh.org/pdf/GunBuyback_Panel.pdf) appear to be essentially regressing the change in the death rate to the change in guns from a gun buy back in Australia, at ...
3
votes
2answers
1k views

Regression on a constant

If I have observations of $y_{i}$ and $x_{i}$ which are i.i.d. I also have OLS assumptions such as $E(\epsilon_{i} \mid X_{i})= 0$, my qustion is: If I project $y_{i}$ onto a constant $\mu$, that is, ...
3
votes
1answer
670 views

What is a good proxy for government quality?

Is it ok to use corruption as a proxy for government quality?
3
votes
3answers
274 views

Intuition behind fixed effects estimator

I understand that the fixed effects estimator in a panel model (say, individuals, $i$ across years, $t$) can be understood either as a including a dummy for each $i$ or running OLS on the time demean-...
3
votes
2answers
129 views

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 ...
3
votes
2answers
52 views

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 ...
3
votes
1answer
41 views

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 ...
3
votes
3answers
4k views

What is the difference between a transitory and a permanent shock?

In my study of time series regression models in econometrics, we are discussing basic time series regressions and interpreting the effects of shocks in finite distributed lag models. I was wondering ...
3
votes
3answers
171 views

Can I use calculated data for regression

Can I use calculated data for regression analysis. case 1: first run OLS $y = \alpha+\beta x$, and get $\hat\beta$, then calculate $z = h^\hat\beta$, at last run $m = \gamma + \mu z$. case 2: follow ...
3
votes
1answer
643 views

Regression with weights

I have a question regarding weighing observations by importance. Suppose I am running the following regression:$$log(y_{it}/y_{it-1})=\alpha+\sum_{i=1}^{N}\gamma_{i}Country_{i}+u_{i}$$ where ...
3
votes
1answer
97 views

How to find the long-run relationship using this regression (3rd time posted)

This is an old exam question I can't figure out. I thought to find the relationship you would sum the coefficients on the Ys, so it would be 0.80 + 0.70 - 0.10, giving you C = 1.4Y, but this isn't ...
3
votes
1answer
58 views

Transforming a matrix of explanatory variable in regression

Given the partitioned regression equation (into $X_1$ and $X_2$), I want to transform $X_1$, say $X^*_1$, such that $X_2$ and $X^*_1$ becomes orthogonal ie. $X_2^T$. $X_1^*$= 0. A matrix can be ...
3
votes
1answer
42 views

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 ...
3
votes
1answer
94 views

Regression - Testing for autocorrelation in the presence of heteroscedasticity

I have constructed a linear time series regression model and estimated the parameters by applying OLS. I now want to test wether the assumptions for proper large sample inference (asymptotic Gauß ...
3
votes
2answers
116 views

interpretation: linear regressions with both unit dummies and time dummies

Suppose I have a panel data with N units and T time periods. For model 1 with only unit dummies: $$y_{it} = \text{intercept} + \beta_1 x_{it} + \sum_{j = 2}^{N}\delta_j I\left(i = j\right) + \text{...
3
votes
1answer
77 views

How do I calculate the impact of an independent variable on a dependent var. when the independent var. changes from 0 to some positive value?

I will try to explain my question using two production functions here. Let $Y$ = Yield of a certain crop (tons/hectare) Assume yield (output) is a function of two inputs, $Y = f(N,I)$, where $N$ = ...
3
votes
1answer
408 views

Does it make sense to 'deflate' a sectoral price index in a regression analysis?

For instance, if one is running a regression with deflated prices for a given year and one of the independent variables is a price index for a given sector, does it make any sense to 'deflate' this ...
3
votes
1answer
53 views

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 ...
3
votes
0answers
141 views

Partial R2 and contribution of Regressors

I asked a similar question on Cross Validated, but got no answer. The following question is sufficiently different. Consider the following deterministic relationship:$$Y_{t}=C_{t}+I_{t}+G_{t}+(X_{t}-...
3
votes
1answer
623 views

What happens when I leave out empty cells in regression?

I'm using Stata 14.1 to do a regression, and I got a matsize too small error. It gave some more output to tell me possible reasons for this problem, and I think ...
2
votes
2answers
1k views

Why isn't the “annihilator” matrix a zero matrix?

I am struggling to understand why M is not null since: $$\mathbf M=I−X(X′X){^-}^1X′=I−XX{^-}^1X'{^-}^1X′=I-I=[0] $$ What's wrong with that reasonning?
2
votes
2answers
176 views

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 ...
2
votes
2answers
58 views

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 ...
2
votes
2answers
76 views

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 $b$ ...
2
votes
1answer
40 views

rotating and exchanging x for y's in regression

I was just wondering what happens generally if i send all my x points to y's and y's to x's (i.e reflect along the y=x line) - if I change the x's and y's will my old error minimizing line still be ...
2
votes
1answer
64 views

Confidence Intervals for Elasticity in Simple Linear Regression

I'm pretty sure this is a very simple question that I am missing something obvious. I have a simple linear regression with multiple independent variables. I want to calculate the elasticity (no ...
2
votes
1answer
27 views

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 ...
2
votes
2answers
232 views

How do I choose the correct model for a regression?

So the central question of my project is to what extent does a country's level of export contibution towards GDP (i.e. exports as a % of total GDP) affect its GDP growth. I'm comparing this ...
2
votes
1answer
38 views

Principal component analysis interpretation

Suppose a wealth index is computed using information on a set of 14 assets that a household possesses. The index is generated using principal components, as the 14 individual asset variables are ...
2
votes
2answers
76 views

Specification bias - estimated variance is biased estimator of true variance of error term

Consider the two models $ (a) y = X\beta + u $ where $X$ is $n \times K$ and (b) $y = Z\gamma + \omega $ where $Z$ is $n \times r$. Under classical assumptions (and $Z$ and $X$ are non-stochastic) if ...