0
votes
1answer
10 views

Impact of lagged values on identity variable

Let's say I'm working with the following simplified macroeconomic accounting identity Y_t = C_t + I_t + G_t, meaning that GNP in time ...
2
votes
0answers
29 views

Causality in microeconometrics versus granger causality in time-series econometrics

I understand the causality as used in microeconomics(in particular IV or regression discontinuity design) and also the Granger causality as used in time-series econometrics. How do I relate one with ...
2
votes
1answer
46 views

My fixed effect model and methodology

I'm doing my master thesis on FDI effect on Chinese wage inequality. I am new to quantitative econometrics so I have no idea if my wage equation is correct. $$W_{it} = β X_{it} + λ_t + η_i + ε_{it}$$ ...
2
votes
1answer
37 views

What does “AR(p) filtered series” mean?

I guess this means that omitting some variables in a certain interval, say, $(x_1, x_2, x_3, x_4, x_5) \to (x_1, x_5)$ in AR(4) model. Is it right? Or does this means eliminating autocorrelations ...
0
votes
1answer
37 views

Which arma model is best one?

I am studying ARMA models. ARMA(25,25) or ARMA(1,1) which one better model? Why? I think that the reason is the ommission of irrelevant variable
1
vote
0answers
112 views

Fitting ARMA model with MATLAB R2012b

I want to fit an ARMA model on a time series (quarterly log returns of a 10 year bond) using MATLAB R2012b. This is part of an exercise. I have problems with the code and the interpretation of a ...
1
vote
1answer
93 views

Cross-correlation in Matlab

What is the difference between: 1) xcov(x,y,10,'unbiased')/sqrt(xcov(x,x,0,'unbiased')*xcov(y,y,0,'unbiased')); 2) xcorr(x,y,10,'unbiased'); 3) [A, B] = crosscorr(x,y,10); ? I think (but I am not ...
1
vote
0answers
41 views

Best data series to teach time series econometrics?

I will be teaching a short course on time-series econometrics to third-year undergraduates. It will be part theoretical, part applied (students using econometrics software). I am looking for great ...
1
vote
2answers
100 views

How to determine the correlation between 2 time series while controlling for a 3rd?

I would like to determine the relationship between two variables after controlling for a third. Specifically, I want to know if the prices of mercury and gold over time are correlated with each other ...
2
votes
1answer
101 views

Pros and Cons: Methods for Detrending Time Series Data

My memory is fuzzy on the advantages and disadvantages of various methods for detrending time-series data. I'm looking for a succinct summary of why and when one should or should not use the ...
2
votes
1answer
93 views

Significance of an impulse response function

I've read several paper that all compare different cumulative IRF of the same VAR equation for statistically significant difference. The IRF they use are simply the sum of the coefficients of the VMA ...
0
votes
0answers
35 views

Is there a formula to find the MAPE for $Y_t$ if we know the MAPE for $\Delta$log($Y_t)$?

Is there a simple formula to find the MAPE for $Y_t$ if we know the MAPE for $\Delta$log($Y_t)$ ~ iid N($\mu$,$\sigma^2$)? Is there an algebraic relation between the two? What if I use RMSFE ...
2
votes
1answer
62 views

Why is the expection of $E(Y_{T+1}|\Omega_T)$ greater than or equal to its previous value?

Consider the following model for $Y_t$: $\Delta$log($Y_{T+1})$ = $u_T$ where $u_T$ ~ IID Normal(0,$\sigma^2$). I want to forecast $Y_{T+1}$. Taking exponentials and then expectations, we see that ...
0
votes
0answers
34 views

Finding a leading indicator of a time series

I am interested in finding a leading indicator of $Y_t$. Is it sufficient to find a variable $X$ for which its lagged value is correlated with $Y$? Do I have to give consideration to the spurious ...
0
votes
0answers
17 views

Correlated historical time-series with missing data

I am trying to propose a method of determining whether health quality changed between 1700-1820 (roughly) in the United States. Some available data/time-series include: mortality rates, height, life ...
2
votes
1answer
82 views

Can this be modelled?

Context: USA economy Background: Its generally accepted that the growth of e commerce has certain curbing effects on the CPI-inflation. Because search costs are much lower online, people always go ...
2
votes
0answers
53 views

Estimating a VAR model with variable coefficients

I want to estimate a VAR model based on the Dufour and Engle paper "Time and the Price Impact of a Trade" (2000). There, the parameter $ b_{i} $ of the endogenous variable $ x_{i} $ is dependent on ...
1
vote
1answer
66 views

Diagnostic for VAR model. non normal

I have some problem about my model. my model is based on VAR. (vector auto-.) well, I've tested ARCH test, BG test(autocorrelation p) and jarque.bera.test. Model is stable. Also I got good result for ...
0
votes
0answers
51 views

Help with panel-data in excel

I want to know if the initiation of a state Renewable Portfolio Standard affects the level of renewable energy output in that state. I don't have access to Stata right now, so I'm stuck using excel. ...
6
votes
3answers
154 views

Does zero correlation between 2 differenced series implies no cointegration between original series?

The question is related to this one. In this question @mpiktas gives an answer on why checking correlation is not enough but the answer doesn't seem completely correct to me for the following reason: ...
0
votes
2answers
177 views

Non-stationary series keep close to each other but correlation between growth rates is ~0 - how is this possible?

I have 2 (monthly) time-series that look like this: Economical intuition suggests that they are positively related and I can see this on the plot but if I compute correlation between their ...
1
vote
5answers
170 views

Can you develop an econometrics model for stress test purpose only focusing on 2008-2009 data?

I have become aware that a group at a large corporation is developing an econometrics model to forecast sales of their product. They are using this model solely to estimate sales in specified stress ...
5
votes
1answer
116 views

Spurious correlation

I've read that if two time series, $Y_t$ and $X_t$, are trend stationary, then regressing $Y_t$ on $X_t$ results in a spurious regression because of an omitted time trend variable. Let $Y_t = \delta_0 ...
1
vote
1answer
94 views

$R^2$ from a regression of two trend-stationary processes, $Y_t$ and $X_t$

In Estimation and Inference in Econometrics, by Davidson and MacKinnon, p.671, they claim that $R^2$ from a regression of $Y_t$ on $X_t$, where both time series are trend stationary, tends to 1 as $n$ ...
0
votes
1answer
122 views

Interpreting the coefficients of ARCH Lagrange Multiplier Test

I am new to econometrics and I am building my first econometric model. I ran the LM test on a univariate time series data of 12000 observations and got the following stats: ...
0
votes
0answers
121 views

Forecasting when the dependent and independent variables are differenced

Consider the following model for $Y_t$: $\Delta$log($Y_t)$ = $\beta_0$ + $\beta_1$$\Delta$$log(X_t)$ + $u_t$ where $u_t$ ~ IID Normal(0,$\sigma^2$). I want a forecast for $Y_{T+1}$. Thus, I need a ...
0
votes
1answer
120 views

Pooled OLS with time-variant regressors

Could someone please explain how a pooled OLS is set-up when the regressors are aggregate variables that are time-varying only (i.e. do not vary for the cross-section at each time t)? If the pooled ...
0
votes
0answers
96 views

Running time-series regressions on a dataset with large gaps: is it legitimate?

I would like to run a plain-vanilla time-series regression, to estimate the sensitivity of my dependent variable to a set of explanatory variables. However, instead of running the regression on the ...
2
votes
2answers
118 views

One time series tends toward the (linear) function of another time series, how to find that function?

I have two time series $p_t$, the daily market price of a particular kind of good $f_t$, the daily production of such good Now assume that there is a unique relationship that tells you the optimal ...
1
vote
1answer
81 views

Insignificant VAR coefficients

I am not quite familiar with vector autoregression (VAR). I am thinking of using VAR/IRF (impulse response functions) to illustrate the relations between some time series variables. However, most of ...
0
votes
0answers
31 views

forecasting export - methods

I have Product X Export data (time series data: year - amount) approx for last 10 years for my country and also Product Export data for Enterpise Y. I am writing thesis. This would not be the main ...
1
vote
1answer
125 views

Program Impulse Response Functions for VAR

I'm trying to program impulse response functions for a VAR model using Cholesky decomposition. The thing is I do not completely understand how I should do this when I read in the literature. Suppose I ...
1
vote
3answers
78 views

Adding up events in time series forecasting

Let us say that we have an event - variable (1/ 0) that denotes the occurence of an event on a daily basis e.g. a strike. Let us now say that we have a continuous variable (sales) that that we want to ...
1
vote
0answers
116 views

I have two sets of data (regular time intervals) is there any way to find out when they correlated the most and when they don't?

Sorry if the title is a bit vague however, i'm not sure exactly how to make my sentence concise. I have two times series: Amount invested into Iraq across time (in months) Price of a stock across ...
3
votes
1answer
2k views

Cannibalization of product sales

I am trying to determine the rate of cannibalization of product sales for A with product B. I am using ~ 2 years of daily sales data for product A and then ~8 months of data for product B. That is, ...
1
vote
1answer
130 views

What's a stationary VAR?

What is a stationary VAR (vector autoregression)? Can a VAR with non-stationary variables be stationary? How do you test whether a VAR is stationary or non-stationary? (Example in ...
1
vote
2answers
243 views

Johansen's $\Pi$ is full rank except variables are non-stationary

I have two variables. They're both $I(1)$ even when I fit constant and trend terms into the ADF test. The $p$-values for the stationarity tests are around 0.5 so it's not a marginal case. However, ...
2
votes
0answers
99 views

How to test for integrated order 2/non-stationary I(2)?

How do I apply the Augmented Dickey-Fuller (or alternative) test to determine if a variable is $I(2)$ instead of $I(1)$? Is there functionality for this in R ...
1
vote
2answers
184 views

Putting stationary variables through Johansen procedure

Is it okay to feed $I(0)$ variables into the Johansen procedure? I've read three sources that seem to state that this is not what you're supposed to do. However, whenever I've done this, I notice that ...
4
votes
1answer
258 views

Multicollinearity in OLS

I am reading Greene's textbook Econometric Analysis where he says that, if there's multicollinearity, then: Small changes in data lead to large swings in parameter estimates. Coefficients have high ...
0
votes
1answer
208 views

Dummy interaction variables are always non-stationary?

I want to know why we can include dummy interaction terms into time series models if they're always non-stationary? For example let $X_t$ be $I(0)$, $X_t \sim N(\mu,\sigma^2)$ and $D_t \in \{0,1\}$. ...
12
votes
2answers
278 views

Irregularly spaced time-series in finance/economics research

In financial econometrics research, it is very common to investigate relationships between financial time series that take the form of daily data. The variable will often be made $I(0)$ by taking the ...
1
vote
2answers
337 views

Detrending a time series regression model

In my text book is says: Regress each of $y_t, x_{t1}$, and $x_{t2}$ on a constant and the time trend $t$ and save the residuals... What do they mean regress each on a constant? What constant ...
6
votes
2answers
3k views

Which Dickey-Fuller test should I apply to a time series with an underlying model that includes an intercept/drift term and a linear time trend?

Short version: I have a time series of climate data that I'm testing for stationarity. Based on previous research, I expect the model underlying (or "generating", so to speak) the data to have an ...
0
votes
1answer
58 views

Removing economic effects from time series

I am analyzing the number of donors cancelling commitments as a monthly time series which varies significantly with economic indicators, some according to internal data, and maybe according to season. ...
1
vote
1answer
607 views

Cointegration testing with a dummy variable

I have the model: $y_t = \alpha + \beta_1 x_t + \beta_2 D_t x_t + \epsilon_t$ With $y_t$ and $x_t$ as $I(1)$ processes, and $D_t =1$ during a large financial crisis, $D_t = 0$ during non-crisis ...
1
vote
1answer
176 views

Quantile regression with dummy variable that's equal to 0 over most $t$

I have the model $Y_t = a + b*X_t + c*D_t + e_t$, where $t \in T = \{1,...,3000\}$ and $D_t$ is a binary variable equal to $0$ over $T \backslash \{20,21,...,30\}$, and equal to $1$ over ...
3
votes
0answers
174 views

Determining smoothing parameter in HP filter for hourly data

I'm trying to determine an smoothing parameter for the Hodrick-Prescott Filter. I've seen that there are papers on the topic, but they are far too advanced for my comprehension. If I have a data set, ...
3
votes
0answers
218 views

Time Series: correcting the standard errors in a huge panel time series data set

I have stock returns at every 5 minute interval of each trading day for over 2 years for 40 stocks. I want to run a Fama-Macbeth regression by time interval (5min intervals) and then correct the ...
0
votes
1answer
214 views

My data passed Johansen test, but they couldn't pass Phillips-Perron test. Why?

I want to choose two-pairs for pairtrading. For pairtradings, two pairs need to pass two tests, the Johansen test (for cointegration) and the P.P. test (for stationary). As I knew, if they related in ...