1,285 reputation
416
bio website stackoverflow.com/users/…
location
age
visits member for 1 year, 11 months
seen yesterday

Aug
30
comment Modeling a non-stationary bounded series
@ Alecos: to check whether the bounded series is stationary or not.
Aug
30
comment Modeling a non-stationary bounded series
The conventional unit root test is not applicable in case of bounded series : see the paper Testing for unit roots in bounded time series
Aug
17
accepted Rule of thumb to rule out reverse causality in the OLS model
Aug
17
comment Rule of thumb to rule out reverse causality in the OLS model
Thanks Dan for the answer.
Aug
15
comment Rule of thumb to rule out reverse causality in the OLS model
Thanks gmacfarlane. Are you implying that the estimated coefficient can not be used as a rule-of thumb to detect endogeneity?
Aug
15
comment Rule of thumb to rule out reverse causality in the OLS model
Thanks Dan. But, my question was not about solving the problem. My question was, whether the simple correlation or simple regression can be used as a rule-of-thumb to rule out reverse-causality.
Aug
15
revised Rule of thumb to rule out reverse causality in the OLS model
added 103 characters in body
Aug
15
asked Rule of thumb to rule out reverse causality in the OLS model
May
21
comment What is the correct procedure to choose the lag when performing Johansen cointegration test?
Have a look at: A Bivariate Causality between Stock Prices and Exchange Rates: Evidence from Recent Asia Flu: CLIVE W.J. GRANGER, BWO-NUNG HUANG, AND CHIN WEI YANG
May
18
awarded  Revival
May
7
comment How do you choose the order p and q for ARMA(p,q) process for modeling a time series?
Have a look at standard time series econometrics textbook like Hamilton (1994) or Enders (2005).
Apr
29
awarded  Popular Question
Apr
26
comment Causality in microeconometrics versus granger causality in time-series econometrics
Given T=20, I think there will be omitted variable bias because of ignoring long run information (error correction term) if the series are cointegrated. As in your example, if the treatment changes in different states and different times and if this treatment is cointegrated with the outcome, then obviously your dynamic model suffers from omitted variable bias. The question is whether the treatment, since it is a dummy variable, can be considered I(1). Alternatively,you consider treatment as an exogeneous variable in long-run and short-run eqns and obtain causal effect (long run and short-run)
Feb
22
awarded  Revival
Jan
14
comment Linearity between predictors and dependent variable in a linear model
The multicollinearity is the problem only when the explanatory variables are highly correlated. One way to test this is to use variance inflation factor or condition index.
Jan
7
answered AIC guidelines in model selection
Jan
7
comment Is it true that $E[e^{tX}] \le e^{E[t^2X^2/2]}$?
I think this has something to do with Jensen's inequality: en.wikipedia.org/wiki/Jensen%27s_inequality
Dec
5
awarded  Notable Question
Nov
23
accepted Graphs in regression discontinuity design in “Stata” or “R”
Oct
11
awarded  Yearling