The tag has no usage guidance.

learn more… | top users | synonyms

0
votes
0answers
11 views

Use DTW-approach for correlation coefficients

Dynamic time warping is a popular similarity metric which I use to find correlations between time series that have different length or are time shifted. As it is a similarity metric, it doesn't show ...
1
vote
0answers
31 views

How to Calculate Standard Error and Prediction Intervals for ARMA Forecasts on Transformed Data?

I have been recently learning about the Box-Jenkins process for ARMA modeling, and I ran into a bit of a wall when it comes to error analysis. In a lot of my data sets, I have to apply a log ...
0
votes
1answer
38 views

Granger causality - lag=1?

I have a question related to Granger Causality testing. Is it okay to use a lag-length of lag=1 in my Granger-test? The optimum lag length selection in my R ...
3
votes
1answer
177 views

Does using lagged independent variables makes sense?

While it seems quite common to calculate a lagged version of the dependent variable and to use it on the right hand side of a model (e.g., autoregressive models), I have rarely seen that lagged ...
0
votes
0answers
15 views

Estimations that can't be applied to models with time operators (lagged)

Some estimation commands can't be applied to models with time operators such as lags. For example, in panel data a model that specifies an impact of independent variables at time t-1 on dependent ...
0
votes
1answer
20 views

VAR lag selection heavily depends on maximum lag investigated

I am fitting an Error Correction Model with two monthly price time series. In Stata I am using the varsoc command to determine the number of lags that are ...
2
votes
1answer
48 views

Simulating a time series including a shock

I want to simulate a time series in R, following an ARMA(1,0) model in the form $Y_t = Y_{t-1} + \epsilon_t$, shocking it at time 20. In a few words, I therefore have to input $\epsilon_{20} = 30$ ...
1
vote
0answers
19 views

Right way to use lags?

I came across a study that analyzes firm performance. Specifically, it aims at answering the question if firing a CEO leads to better performance. In the study, the author splits the sample into two ...
1
vote
1answer
28 views

Modelling a time-series with lags

I have a data set with 200 predictors and 700 observations. It is a regular time series, so 700 days in my case. I want to experiment with lagged variables, which I will create manually and save as ...
1
vote
1answer
24 views

R: Access/store optimal number of lags from unit root test [closed]

I am testing several variables for unit roots via the ur.df (from urca package) and CADFtest ...
0
votes
0answers
27 views

Level or Diff data for lag selection criteria?

I am doing granger causality for oil price and exchange rate using Eviews. I would like to ask if my data is stationary after 1st diff for both variables after using unit root test, then should i use ...
0
votes
0answers
143 views

Lag length selection in a dynamic model, ARDL approach to cointegration in R

I want to programme an ARDL approach to cointegration in R. Below is the generic equation: $$\Delta y_t=\beta_0+\sum \beta_i \Delta y_{t-i}+\sum \gamma_k \Delta x_{1,t-k}+\sum \psi_j \Delta ...
1
vote
0answers
46 views

Breusch-Godfrey Test and the length of the lag, p

I'll use Breusch-Godfrey (BG) test to test correlation of an AR(1) model. In order to perform a BG test, the simple regression model is first fitted by ordinary least squares to obtain a set of sample ...
1
vote
1answer
57 views

Why after including lags do seasonal dummies become significant?

I am trying to model data that clearly looks like it has seasons. However I only pick up seasonality in very small subsets of the data and only after I add in lagged variables and eliminate trend. I ...
1
vote
1answer
63 views

What are the implications and possible explanations for an AR(7) process model?

I am in the process of constructing a regression for financial data and found that serial autocorrelation is present in the model through the correlogram: It looks like it could be an AR(7) ...
0
votes
0answers
26 views

Inverse of Lag Operator

I'm new to the concept of a "lag operator" $L$ where $Ly_t=y_{t-1}$ for some sequence $\{y_t\}_t$. Question: How do you prove both equalities below: $$ (1-\lambda L)^{-1}=1+\lambda L+\lambda^2 ...
0
votes
2answers
49 views

DLNM and crossreduce(): getting the coefficients behind the cross-basis

I am using the R package dlnm to fit a distributed lag non-linear model estimated with lm(). One can specify both the exposure ...
0
votes
0answers
19 views

How much should lags be used in GMM?

what are the necessary conditions for the use of lags in GMM and to what extant the lags should be use? is there any limit for the lags in GMM? i know its pretty question but due to my limited ...
1
vote
0answers
38 views

VAR Stability - Lag Order Selection

I followed this excellent tutorial on the implementation of Granger causality: http://davegiles.blogspot.de/2011/04/testing-for-granger-causality.html and applied the method with an R script. My date ...
0
votes
1answer
105 views

Lag Length from a VAR and Vector Error Correction Model (VECM)

A colleague wrote a paper and I am reviewing it for him to make sure it is good. In the paper, the author estimated a VAR to determine the optimal lag length based on the Schwartz Criterion. Then ...
1
vote
1answer
37 views

Reciprocal Causation in Panel Data

I have weekly data on stop and searches for all London Boroughs for ten years (N=32, T=566) and am interested in whether the number of stop and searches has any impact on crime rates. I don't expect ...
0
votes
1answer
45 views

Degrees of Freedom in VAR

A colleague of mine is using a VAR for quarterly data (deseasonalized). Typically it is customary to use lag of 4 or 5. However, they used two lags based on a single test result, the SC criteria. Of ...
2
votes
1answer
137 views

Is an auto-correlation plot suitable for determining at what point time series data has become random, and how does one interpret the plot?

A piece of research I am working on requires us to decide at what point time series data has become random. For what it is worth, the time sequence in question is a collection of in-process timings ...
4
votes
0answers
154 views

Fixed Effects vs Lagged DV vs. First Differences Regression

What are the differences between using unit fixed effects, unit fixed effects and time fixed effects, lagged DV, or first differences to analyze a time series with 4-5 time periods and 35-50 units per ...
0
votes
0answers
84 views

Forecasting time series with lagged variables and machine learning

I want to forecast a time series based on the lagged variables of the model and train it using a machine learning algorithm like Random Forest, SVM, Neronal Network, etc. So I want to forecast A ...
0
votes
0answers
11 views

Deciding the lag while testing for timeseries data stationarity

I am currently reading up on time series forecasting using ARIMA in SAS. I just began to go through what has been explained here : ...
2
votes
0answers
36 views

Lag Selection in an unbalanced panel in R

How to determine appropriate number of lags in an unbalanced panel? Thanks.
0
votes
0answers
114 views

What is the difference between “lag order” and “maximum lags”

The R Vars package has a Vector Auto Regression function called var. The arguments include (among other things) "p" defined as the "Integer for the lag order" and "lag.max," which is defined as ...
1
vote
0answers
37 views

CCF time lag in minutes in R

I have data sampled every 5m and I want to estimate the ccf between them, in order to do it I prewhiten the time series x and y and then I apply CCF But lags are not direct related with my sampling ...
0
votes
0answers
20 views

Estimate VAR model from data about lags

Does anybody have any idea how i would write the var model based on this table? What coefficients should be included? Any hint will be much appreciated. Thank you!
1
vote
1answer
73 views

Finding optimal lag order for an exogenous regressor in a VAR model

I can't use VARselect as it gives lags in a VAR model which considers all the variables to be endogenous. In my case, one of the variables is exogenous and affects dependent variable with a certain ...
4
votes
1answer
340 views

Distinguish between short run and long run effects

I read in a paper the following sentence: The fact that there is a difference between short-term and long-term coefficients is a result of our specification which includes lagged endogenous ...
1
vote
1answer
124 views

Lag length selection for a VAR model

The model I am working on has 4 time series (X, X1, X2, X3). Lag lengths are 5, 1, 4 and 6, respectively. X1, X2 and X3 are stationary at level and X is stationary at second difference. I am applying ...
2
votes
1answer
998 views

Lag selection for Augmented Dickey Fuller test

Apologies in advance, I am a beginner so these questions might be quite simple. I am testing log real exchange rates for unit root stationarity for EU15 countries. I was wondering what is the best way ...
0
votes
0answers
96 views

lag number in VAR

I am trying to determine the optimal lag number in 2-equation VAR as follows: 1. choose lag based on information criteria 2. estimate the model using # of lags determined above and test for ...
0
votes
0answers
69 views

Using lag of variable as a proxy to remove endogeneity- Can I just replace the variable in OLS, or do I have to use 2SLS?

I am running a regression of capital, labour and level of migration on GDP (augmented Cobb Douglas production function). To counteract the endogeneity between migration and GDP (migrants might move to ...
0
votes
0answers
96 views

how to specify range of lag in prewhiten CCF using package TSA in R

I am doing time series regression using package TSA in R. I have 2 time series, say x and y, so I started by doing prewhitened CCF. So, 2 issues I have encountered and would really appreciate if any ...
0
votes
1answer
383 views

How many lags should I include in the VAR-model

When building a VAR-model with six variables I had the following situation: after building a VAR(1) the overall portmanteau test says that the residuals are ok (p=0.85, p_adjusted=0.22). But when I ...
0
votes
2answers
92 views

Conditional entropy and Spearman's correlation based lag in time series

I have two time series A, B. Both are seasonal and B primarily is A driven( other temporal causes may exist). B-Red, A- Green I want to calculate lag of red series with respect to green as clearly, ...
0
votes
0answers
106 views

Time domain regression - determining lagged predictors

Determining lifestyle factors affecting a medical symptom I have a dataset with n=200 records corresponding to contiguous days and consisting of 1 continuous output variable (a medical symptom) and ...
0
votes
0answers
87 views

Logit: using lagged dependent variable

Is it methodologically feasible to include lagged dependent variable in the logit model?
3
votes
0answers
375 views

How to use lagged dependent variables (panel data) in practice?

Working with a panel data set with a daily time series structure I was told to include a lagged dependent variable. The dependent variable is daily electricity consumption of a medium size sample ...
1
vote
1answer
229 views

AIC/BIC values keeps falling as I add more and more lags. How do I select the appropriate lag length?

I am trying to minimize the values of the Akaike and Bayesian Information Criteria to figure out the optimal lag structure for my ARDL error correction model. I am using Stata to run my analysis and ...
0
votes
2answers
165 views

R² of 1 with dynlm procedure?

Dear statisticians/programmers, I want to model the price of AXE deoderands in Albert Heijn (a dutch supermarket) as a linear function of its own past (up to two lags) and the past of the price of ...
3
votes
1answer
161 views

Goodness of fit for a spatial panel with fixed effects and both spatial lag and spatial error

On a dataset, I performed spatial panel regressions with fixed effects, and with both a spatial lag and a spatial error (both are significant), using package splm in R (Millo and Piras 2012 Journal of ...
2
votes
0answers
271 views

How do I choose the optimal number of lags?

I am making a model (multiple regression) that predicts credit growth. Many of the independent variables are leading indicators and should therefore be lagged. How do I choose the optimal number of ...
1
vote
0answers
63 views

What type of model should I use? (Time series, univariate, dependent variable is a count)

I have a univariate model in which I am looking to predict the number of articles per week in a newspaper about a protest (count data) by how many arrests of protesters occurred per week. I have 148 ...
1
vote
1answer
403 views

Regressing a differenced variable on a lagged variable. How can I fix the error in R?

I have a time series (std) of 324 observations with no missing values, starting from January 1987 and ending in December 2013. I want to regress via OLS the one in the question. In R, the code: ...
5
votes
2answers
480 views

Residual autocorrelation versus lagged dependent variable

When modeling time series one has the possibility to (1) model the correlational structure of the error terms as e.g. an AR(1) process (2) include the lagged dependent variable as an explanatory ...
1
vote
1answer
200 views

Specifying lag in `dlnm` when passing arguments to `crossbasis`

I am using the dlnm package to build a finite distribute lag linear model. I intend on testing the model-fit based on various lag levels to assess which lag is ...