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Questions tagged [econometrics]

Econometrics is a field of statistics dealing with applications to economics.

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Question Regarding Zero Conditional Mean

Hi I am a beginner to econometrics! I have been dealing with bivariate regression. We use the formula $y = \beta_0 + \beta_1 x$. I am told that if $E(u\mid x) \ne 0$ then the estimate of the slope ...
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1answer
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How to test whether a statistically significant coefficient is driven by observations in certain periods in panel data?

I estimated a fixed effects model as follows using a unbalanced panel with 10 years of observations. $y_{it}=\beta x_{it}+\delta_i+\gamma_t+\epsilon_{it}$ The coefficient of interest is $\beta$. I ...
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9 views

GMM moment conditions [on hold]

I want to know why it is useful to add the moment condition about $E(X^2Y)$ for deriving parameters in linear regression.
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0answers
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Can you use two dummy variables?

Is it possible to use two dummy variables for breakpoints in a linear regression? In EViews I've created the following: ls log(consumption) c log(gdp) log(gdp(-1)) log(consumption(-1)) @year>1989 @...
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Including all rows for an ID if ID meets a condition once in panel data in R [migrated]

I'm sorry if a similar question has been answered already but I can't seem to find any posts helping me. I wish to define two separate intervention groups (linked to this previous question I asked ...
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1answer
24 views

What's the point in using identity matrix as weighting matrix in GMM?

What is the point of using the identity matrix as weighting matrix in GMM? GMM is the minimizer of the distance $g_n(\delta)'\hat{W}g_n({\delta})$, where $g_n = \frac{1}{n}\sum_ix_i\epsilon_i$. If we ...
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1answer
28 views

How important is a statistically significant intercept?

I've created the following model: log(consumption) = a + b*log(GDP) + c*log(GDP(-1)) + d*log(consumption(-1)) The slope coefficients are all statistically ...
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0answers
16 views

Tobit versus OLS, is dependent variable censored?

I would like to investigate possible relationships between arbitrage profit of crypto exchanges and exchange's order book characteristics, such as volatility, spread, liquidity. I compute the ...
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1answer
24 views

Splitting panel data into subgroups

I have a (an unbalanced) panel dataset of individuals over different periods of time (one time period = one month). I'm attempting to analyse the effect on the level of activity of the individuals of ...
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0answers
11 views

Would my exclusion restriction be satisfied with this instrument?

I want to estimate the impact of home internet use on hours worked. Due to endogeneity concerns, I was thinking to use an IV approach. One instrument I have seen in similar literature and was ...
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1answer
25 views

Q: Implications of autocorrelation in a Dickey-Fuller unit root test

I am conducting a Dickey-Fuller unit root test on the FEDFUNDS series from the FRED database. My estimation period is quarterly from 1955(1) to 2007(4) (taking the average of the monthly rates within ...
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0answers
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2sls asssumptions vs IV assumptions

Silly question but I was confused about the independence assumption for instrumental variables when they are used in 2SLS. Is it the case that the instrumental variable used in 2SLS only has to be as ...
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0answers
15 views

How do I cluster my standard errors in a triple differences approach with two clusters?

I am trying to estimate this following triple differences regression in order to test for parallel trends in the difference in differences: My treatment is binary (it is a law that was passed in one ...
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2answers
32 views

Is there a mistake in the expression of this variance?

I'm busy reading through an econometrics textbook (page 147), and I don't understand the step $$\mathrm {Var}\left(n^{\frac 12}\left(\hat\beta - \beta\right)\right) = \boldsymbol{A^{-1}}\sigma^2\...
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0answers
20 views

Instrumental variable predicts endogenous variable in an unexpected direction

I am trying to estimate a causal relationship between two variables. I'm concerned about endogeneity, so I'm using an instrument. The instrument strongly predicts the endogenous regressor, however it ...
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19 views

Interpreting marginal effect of interactions in OLS

I have the following model, as you can see I have included an interaction between i.own for 10 dummies and innoscore which is grand mean centred as a way of making interpretation easier. ...
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1answer
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Interpolating principal component

In my thesis, I use PCA from a bunch of WVS responses to measure the social capital of a country (aggregating principal components to country averages). However, WVS provides a quite low frequency of ...
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0answers
16 views

Difference-in-Difference model where treatment intensity increases over time

I'm currently trying to figure out whether a specific Diff-in-Diff model makes sense. Suppose I have a set of 20 countries, where one country (A) introduced a tax for a specific good in 2005 and ...
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0answers
19 views

Covariance Algebra Question [closed]

Consider $y_i=\mu_{t(i)}+u_i$ where $y_i$ is the college gpa of student $i$ who grew up in state $t(i)$, and the state-level latent mean $\mu_{t(i)}$ is uncorrelated with individual level error terms $...
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0answers
24 views

Unclear proof in the Gauss-Markov theorem [closed]

I don't understand a step in the proof of the Gauss-Markov theorem: Mainly, why can we simply replace y with e, given that y is defined as: Thanks in advance!
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2answers
59 views

Moving average process - stationarity

If we consider a moving average process of order 1, is that stationary? Because, although, the mean will remain the same for Yt and Yt+k, the variance and co-variance will change if you calculate ...
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0answers
27 views

What 'level' of fixed effects should I be using?

I'm trying to see the impact of using the internet at home on individuals' hours worked. To address endogeneity concerns, I am using terrain slope as an instrument, as slope makes it more costly for ...
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0answers
14 views

How best to model a complex function like Y=K^a*(cL+dM)^b (lowercase letters to be estimated)

Ok brains trust. I'm trying to model a production function which has an input that decays over 'distance' away from where production takes place. In other words, an input that is 1 unit away is ...
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1answer
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Interpreting regression coefficients when the outcome variable is an inverse hyperbolic sine function

I just learned that when there are zero or negative values, a good alternative to using a logged function is the inverse hyperbolic sine function. When using log transformation on the dependent ...
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0answers
15 views

Maximum Likelihood estimator for GARCH with jump (papers on this topic)

Does anyone know a reference to a paper that would show an actual calibration of GARCH(1,1) model with jumps to a historical time series?
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26 views

Stata: options vce(robust) and vce(cluster)

I have a panel of firm data and my supervisor recommended vce(cluster firmID) for clustering the standard errors. However, the ...
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1answer
23 views

On dummy variable

I am doing a study on determinants of livelihood diversification by using censored Tobit regression model .if I include more than one dummy variable along with quantitative variable,will it cause any ...
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0answers
33 views

How to Estimate Treatment Effects using Heckman two steps (Heckit)?

I need a help on how to find a treatment effects using Heckman two steps method (Heckit), I need to find ATE (Average treatment Effects), TT (Treatment on treated) and MTE. I tried to do a simulation ...
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0answers
39 views

The Efficient Market Hypothesis and forecastability?

According to Wikipedia: The efficient-market hypothesis (EMH) is a theory in financial economics that states that asset prices fully reflect all available information. A direct implication is that ...
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0answers
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Econometric model choice after Breusch and Pagan?

I have panel data and as a new Stata user, I have a question regarding my model choice: After performing a Breusch and Pagan test for RE, the result comes out significant indicating that I am to use ...
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2answers
34 views

What can I consider to choose between the same model but estimated with different estimators?

I estimated a standard regression equation with ML and GMM. The question is: how can I know which estimator provides the best estimate? (e.g., the GMM is more efficient if errors are not normally ...
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1answer
37 views

Why doesn't Total Sum of Squares change when we add up new variable to a regression equation?

I understand the reason for RSS to change, but how about TSS? Is it somehow associated with the constant number of observations?
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1answer
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(Econ) What is the best technique (model) in my case? (FE,RE, etc.)

I am new to Stata and I am using a panel data of 203 firms over 4 years over different countries for my thesis. Time-invariant variables are owner type dummies, an ownership concentration variable, ...
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1answer
30 views

What should I conclude if a Unit Root Test gives contradictory results with & without a trend?

I have a data set for a variable, for which I have run some unit-root tests: ADF (constant/without trend): t-stat=-1.0816, p-val=0.7218 - DNR ADF (constant & trend): t-stat=-4.5203, p-val=0.0021 -...
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0answers
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How do you choose an appropriate time series regression model?

I am working on a research proposal where I want to test the effect of different macroeconomic variables (i.e. government spending, FDI, trade openness, international GDP growth, etc.) on the GDP ...
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Specifying the bandwidth parameter for Local Whittle estimation

In every Local Whittle function I have seen I have to set bandwith parameter usually denoted m such that m = floor(1+T^delta). I am interested in the delta, how do I choose what value to put in the ...
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1answer
35 views

Autocorrelation in residuals

Hi guys, thanks for your time! Problem description: I am working with dynamic factors. I have 4 panels of 24 series (hourly electricity prices) and I reduce them to 1 dynamic factor each that I then ...
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1answer
45 views

Mixed logit random parameters for individual specific variables

It is my understanding that in a mixed logit model there can be two types of variables, alternative specific and individual specific. For example, in a dataset for choices of fishing modes like this (...
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0answers
30 views

Endogeneity versus multicolinearity in regressions?

(I limit myself to two explanatory variables to keep it simple) So as I understand it, when an explanatory variable is highly correlated with another variable then it becomes difficult to distinguish ...
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0answers
68 views

SUR and interaction terms

Suppose I want to determine if a simultaneous model (A) was identified: $y_1 = \beta_{10} + \beta_{11} x_1 + \beta_{12} y_2 + \epsilon_1$ $y_2 = \beta_{20} + \beta_{21} y_1 + \beta_{22} x_2 + \...
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0answers
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Adjusting for ARCH effect in regression analysis

I have the following regression: yt = b0 + b1X1t + b2X2t + b3X3t + e I then saw that e is serially correlated so I modeled the regression with ARIMA errors. However, then I saw that there was an ARCH ...
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0answers
31 views

DnD - Parallel trends in subgroups?

I am estimating a standard two period difference in differences model, where I estimate whether a policy change was associated with an individual level behavior change in a state that implemented it ...
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2answers
37 views

OLS with ARMA errors, tip or two

I need a tip or two. I am performing OLS with dynamic factors (4x1 factors each representing a PANEL of 24 series, hence 4 time series). My OLS has autocorrelation in the error so I want to use OLS ...
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0answers
34 views

What is “identification assumptions” in econometrics? [closed]

I'm starting to study econometrics from Wooldridge's book. But some doubts arise regarding to the role of Conditional Expectations in Econometrics. Wooldridge says that although it is not always ...
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2answers
82 views

Is $(1-L)Y_t=\epsilon_t \to Y_t=(1-L)^{-1} \epsilon_t$ mathematically correct?

Consider an AR(1) model with coefficient $\rho =1$, i.e. a random walk, $Y_t=Y_{t-1}+\epsilon_t$. We usually say that since the AR polynomial has a unit root, it cannot be inverted and therefore the ...
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1answer
34 views

Using GDP to predict Probability of Default [closed]

I would appreciate if you could help me to answer on how to use the GDP (Gross Domestic Product) to predict the probability of default (Probability of corporate defaulting in their payment). By using ...
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0answers
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Given a simple logit panel data model, the MLE estimators are inconsistent

Consider a binary choice model, $P \left( y _ { i t } = 1 | x _ { i t } , \alpha _ { i } \right) = F \left( x _ { i t } \beta _ { 0 } + \alpha _ { i } \right)$, $$F ( z ) = \frac { e ^ { z } } { 1 + e ...
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1answer
47 views

How would heteroskedasticity look like with negative correlation?

I hope I formulated the question correctly, but I am purely interested in heteroskedasticity: cov($e_i$,$e_j$) and not in autocorrelation with the dependent variables. So positive correlation of the ...
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0answers
18 views

How can I interpret two outputs in the Johansen cointegration tests

I got two "weird" (for me) outputs of the Johansen cointegration test with two different groups of variables (each group with three endogenous variables). This is the first ...
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0answers
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How to estimate the MLE for a probit panel data model in R? [closed]

Can you recommend a good package in R to calculate the MLE for a simple panel data probit model? I would like to use GHK simulator to do it. But What I found is not for panel data in R.