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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29 views

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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311 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 ...
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29 views

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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1answer
33 views

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
309 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 ...
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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 ...
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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 ...
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47 views

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
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 ...
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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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135 views

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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84 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?
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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 ...
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1answer
93 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 ...
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1answer
26 views

Ttest and heteroscedasticity problem in no intercept model

I was running a t test over two regression betas with the assumption of equal variance. I know that if the condition of homoscedasticity do not hold then there are chances to have type 2 error but ...
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In panel data application, when using Fama and MacBeth regression is preferable over the fixed or random effect model? thought

When discussing panel data, many econometric books, usually, focus just on fixed or random effect model as means of estimating regression for panel data. Despite this tendency I have seen many papers ...
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25 views

Multiple regression.

How do I plot a multiple regression graph? Shall it be a many dimensional plane(equals to number of explanatory variable)? Or will be the line for each beta, since the slope or beta is the partial ...
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2answers
391 views

Testing for Endogeneity

I apologize if this question is very basic. I have the following plain vanilla Instrumental Variable model. $Y=\alpha+X\beta+\varepsilon$ $X=\delta+Z\gamma+\eta$ $\varepsilon\perp\eta,\quad Z\perp\...
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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 ...
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211 views

Equilibrium Price - OLS Regression

I have asked another question related to price elasticity, which pretty much left me with this problem: I want to analyze the factors influencing the price of a product. The underlying assumption is ...
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2answers
551 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 ...
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2answers
57 views

Conditional independence and no correlation

I have a question regarding basic econometrics. Consider the model $$y_i=\alpha +\beta x_i +u_i$$ I understand that assumption 4 of the linear regression model states $$[1] \quad E(u|x)=0$$ ...
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Marital status determinants

I am looking for the researches that have studied factors influencing marital status probability. I need them for citation purposes. After looking for a long time I have not found anything. So I need ...
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462 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 ...
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2answers
203 views

Monthly average rate of discount, 3 month Treasury bills, Sterling Vs 1 Month

I have been advised by one of my professors to use UK treasury bills for a risk free rate when calculating expected returns for stocks. I wanted to know whether I should be using 1 month T-Bills or 3 ...
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1answer
99 views

Regression with Dummy Variables

When I analyzed a data set with two categories, I used a dummy variable $z=1$ for category 1, and 0 otherwise, and added the extra term $\beta z$ to the regression model. Suppose the least squares ...
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1answer
342 views

Independent identically distributed

When we are talking about the least squares assumptions, one of the assumpions is that (X,Y) are i.i.d. What bothers me is that if we take an example population and research distributions of age and ...
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1answer
641 views

price elasticity: Linear regression low r square

I faced an interview question for a job where interviewer asked me suppose your r square is very low (between 5 to 10%) for a price elasticity model. How would you solve this question? Anything that ...
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1answer
387 views

Fama Macbeth and double clustering presents inconsistent results

I have a large unbalanced panel data with 460 firms and 1259 days. The model I would like to run is below $$ Y_{it} = \beta X_{it} + \alpha Z_{t} + \epsilon_{it} $$ where $Y_{it}$ is stock return, ...
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1answer
120 views

RDD with multiple cutoffs

I am trying to study the effects of a policy on educational attainment of individuals (years of schooling, primary/secondary school completion, literacy). Since the policy starts in a specific year I ...
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147 views

Relationship Input Distance Function and Output Distance Function

I was wondering if anybody knows how input distance functions (IDF) and output distance functions (ODF) relate to each other. One of the advantages of distance functions over cost and revenue ...
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1answer
60 views

Positive interaction term with one negative component?

Say I have an augmented growth regression, where my Y is GDP growth, and my Xs are the classical MRW variables, + international aid + corruption + the interaction term between the two. Basically, I'm ...
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1answer
220 views

Problem of generated regressors [closed]

I use data (adv. labor and wage) through a nonlinear model to recover the unobserved data (use fsolve in Matlab to solve this system of equations) and run a regression of labor (or wage) on these ...
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what mathematical function we can use to show house price changes in time? [closed]

I want to know if I have data of house prices of an area in time, what mathematical function will best fit it's graph? Or in other word, what function I could use that in time $t$, $f(t)$ will be a ...
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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, ...
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133 views

Difference in Regression Discontinuity Estimates

Suppose I run a regression discontinuity design (RDD) for two different samples - say, separately for regions A and B of the same country. I get RDD estimates that are statistically significant in ...
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1answer
239 views

Appropriate estimator for FDI “gravity” model

I am trying to model Foreign Direct Investment (FDI) flows and am facing several issues; There is the well-known condition that under heteroskedasticity log-linearized OLS models are biased and ...
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1answer
46 views

Statistics: Understanding confidence interval [closed]

In R I have used lm()to fit a model. Then I use the confint() function to learn more about the slope. How to I understand the ...
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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{...
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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 $N$ = ...
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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 ...
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1answer
156 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 ...
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28 views

Cannot reproduce paper result on Boston Housing

I have been trying to reproduce the results for "Hedonic Housing Prices and the Demand for Clean Air" but to no avail thus far. In table 7 there are three regressions mentioned using the Boston data ...
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1answer
57 views

Regression of first differenced log-transformed model

I am cosidering to transform a regression equation applying logarithms to the dependent and some of the independent variables (the ones I am actually interested in while leaving unchanged the others ...
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124 views

Interpreting multiple interaction terms

I'm running the following regression on panel data: $ %Translator MathMagic Pro for InDesign Mac v9.14, LaTeX converter, 2016.9.11 22:27 \begin{array}{l} {{\mathrm{tscorek}}_{\mathrm{i}}\mathrm{{=}}{\...
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2answers
71 views

Taking logarithms of variables [closed]

It is common to taking logs of variables when perform a regression analysis. But the observations will become negative after logs transformation when it is less than 1. Is this the possible concerns? (...
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118 views

Calculate coefficient estimates [closed]

I am studying computer science and enrolled in an econometrics class. As of this I have very basic understanding of the subject. I am trying to figure out the following question but don't know where ...
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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 ...
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1answer
63 views

price elasticity of output, makes sense?

I was wondering, in a log-log model of output, labour and commodity price where output is the depedent variable, does it make sense if the coefficient on the price variable is interpreted as the "...
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1answer
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 ...