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
0
votes
1answer
29 views

regression method for data that contain a number of observation for several years

I have a data set about 125 companies. For each company I have the salary and some other variables about the top 5 managers in each company. One observation contains the top 5 managers in each one of ...
2
votes
2answers
70 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 ...
3
votes
1answer
56 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 ...
2
votes
1answer
38 views

Can I treat pooled cross-section as panel data and do regression analysis?

I work with a large survey data that is pooled cross-section, i.e, people interviewed are randomly chosen in each time period. This is not panel data. But, I aggregate the individual cells according ...
1
vote
1answer
54 views

What is the interpration of results if adding or subtracting a control variable effects the significance of explanotary variables?

I am conducting some regressions on economic growth determinants and I am disillusioned. Essentially by choosing what groups of variable to regress I can get the desired significance. What does this ...
2
votes
0answers
27 views

Regression analysis with interaction and decomposed main effect

I'm trying to figure out if I need to include the main effect in a regression analysis with an interaction if I am already including a decomposed version of the main effect. For example, let: ...
0
votes
0answers
20 views

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 ...
0
votes
0answers
32 views

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 ...
0
votes
1answer
32 views

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 ...
2
votes
2answers
57 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 ...
0
votes
1answer
30 views

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/...
0
votes
0answers
12 views

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 ...
3
votes
1answer
662 views

What is a good proxy for government quality?

Is it ok to use corruption as a proxy for government quality?
-1
votes
1answer
44 views

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?
0
votes
1answer
47 views

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 ...
0
votes
0answers
28 views

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'...
0
votes
2answers
45 views

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 ...
0
votes
0answers
9 views

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 ) \...
1
vote
1answer
36 views

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 ...
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 ...
2
votes
1answer
42 views

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 ...
1
vote
1answer
33 views

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 ...
2
votes
2answers
175 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 ...
1
vote
0answers
41 views

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 ...
4
votes
1answer
46 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 ...
3
votes
2answers
70 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
1answer
40 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 ...
1
vote
0answers
16 views

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: $\...
0
votes
0answers
16 views

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. ...
2
votes
0answers
29 views

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+...
0
votes
2answers
86 views

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?
1
vote
1answer
42 views

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 ...
1
vote
0answers
17 views

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, ...
1
vote
0answers
74 views

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 ...
1
vote
0answers
15 views

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 ...
1
vote
0answers
10 views

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 ...
1
vote
1answer
78 views

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. ...
1
vote
1answer
77 views

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 ...
2
votes
1answer
49 views

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 ...
3
votes
2answers
51 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 ...
1
vote
0answers
25 views

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 ...
1
vote
1answer
26 views

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 ...
2
votes
2answers
74 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 $b$ ...
1
vote
1answer
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 ...
4
votes
1answer
281 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 ...
1
vote
0answers
28 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, ...
1
vote
1answer
32 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 ...
4
votes
2answers
292 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
1answer
68 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 ...
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 ...