Questions tagged [dynamic-regression]
Dynamic regression is a type of regression, where one of the independent variables is a lagged dependent variable.
147
questions
1
vote
1
answer
62
views
Why do dynamic panel data models with random effects yield different effects depending on the R package (plm vs lme4)?
[Edited for clarity and detail]
Summary: A random effects model should produced biased estimates for a dynamic panel, but the lmer function of the R lme4 package ...
- 249
1
vote
0
answers
39
views
ARIMAX: only MA(1) model gives meaningful coefficients for exogenous variables
Is it possible that the coefficients for the exogenous variables in (regression with ARIMA errors) are only meaningful with MA(1) models?
Here is my reasoning and a simulation. I would be grateful ...
- 586
0
votes
0
answers
20
views
OLS Model with Lags - logged coeff
i am building a OLS model using python, where the dependant and independent variables are lagged. This is a form of econometrics model where i want to figure out how much each independent variable ...
- 11
0
votes
0
answers
17
views
Lotka-Volterra ordinary differential equation model to describe oscillations in a single observed entity
Background
The Lotka-Volterra model is the starting point for any model of ecological dynamics. It can be described as a set of two ordinary differential equations (ODEs) with varying complexity. ...
2
votes
1
answer
87
views
How to implement Dynamic regression Forecasting using only lagged values of the dependent variable
I understand that Regression with Arima errors which is also called Dynamic regression is normally implemented using exogeneous variables, is it possible to implement dynamic regression using only ...
1
vote
0
answers
159
views
Repeated measures of multiple time series processes
I am struggling with a comparison of temporal processes, which are observed in several time series. The problem is as follows:
Suppose there are some semi-experimental conditions, with several ...
- 11
3
votes
1
answer
68
views
Estimator for Dynamic Panels with Individual Specific Slopes
I'm working on some economic stuff and the objective is to conduct a panel data analysis. I assumed the following data-generating process:
\begin{equation}
y_{it} - y_{i,t-1} = \eta z_{i,t-1} + \...
- 309
0
votes
0
answers
108
views
Dealing with conditional heteroskedasticity in dynamic linear model
I'm working on a regression problem and am struggling to figure out how to deal with the conditional heteroskedasticity present in the error terms. I will try and work through what I have done so far, ...
- 1
1
vote
0
answers
24
views
Quantifying the impact of multiple time series on another time series
I have a few time series that correspond to the popularity of various documentaries about food, and other time series that correspond to outcomes of interest (various dimensions of food consumption). ...
- 193
1
vote
0
answers
39
views
Estimating treatment effect using panel data and absorbing binary treatment
I have a panel dataset of a large N and T = 24. I want to estimate the effect of a treatment (in this case, taking on a certain type of credit product) on Y which is an individuals credit score. I ...
- 11
2
votes
0
answers
26
views
Dynamic panel data model with treatment
Consider a simple dynamic panel model with a single lag: $$y_{it} = \alpha_i + x_{it}'\beta + \rho y_{i,t-1}+\epsilon_{it}$$
Now assuming that $x_{it}$ is most ordinary covariates, this can be ...
- 150
0
votes
0
answers
278
views
Nickell Bias in dynamic Fixed Effect model for large T
From various sources and reading, I get to know that, the Nickell Bias associated with employing fixed effects with a lagged dependent variable is small when T is large. I understand the notions ...
1
vote
2
answers
190
views
Short-term gas demand forecasting
I'm a 22 year old Statistics student with a big problem to solve. English isn't my first language, so I apologize in advance for any mistakes in my grammar.
I'm trying to make a short-term gas ...
- 31
0
votes
0
answers
13
views
Possible statistical modeling method for identifying dynamic influence of different factors over time
I'm trying to build a statistical model which could capture the dynamic influence of different factors over years, for example, customers who buy a specific brand over different years, and I'm trying ...
1
vote
0
answers
34
views
Forecast Assistance given Monthly Time Series Data
I'm looking for some help to determine what type of model I should use for the given data set:
...
- 177
2
votes
1
answer
44
views
Is there a way to tell when a time-series can no longer be predicted by the same model?
I am modeling a time series using a multiple (dynamic) linear regression model. I suspect that at some point, the model no longer accurately predicts the true series. Is there a way to find the point ...
- 75
2
votes
0
answers
48
views
Is there a test/model to tell whether an individual deviates from a group?
I'm working with time-series data on a handful (about 12) of individuals. Under normal conditions, the variable of interest for each individual is correlated among the group, i.e. if ...
- 75
1
vote
0
answers
207
views
Difference between Dynamic Factor Model and Factor Augmented VAR?
One simple question:
What is the difference between the dynamic factor model and factor augmented vector autoregressive (FAVAR) model?
- 149
0
votes
0
answers
205
views
Auto. Arima and ARIMAX for multi variate time series forecasting
I'm trying to do multivariate time series forecasting using the forecast package in R. The data set contains one dependent and independent variable. From the cross-correlation the 0 day lag of the ...
- 123
0
votes
0
answers
58
views
Regression modelling options for time-varying contribution of exogeneous variables
When building a regression model for observations in time $y_t = f(\beta, x_t, \varepsilon_t)$, I want the magnitude of $x_t$ to have different contribution to $y_t$ at different time moments. I ...
- 1,084
0
votes
1
answer
136
views
Can I apply the same DCC-GARCH model on sub-samples to investigate differences in co-movements?
I am using DCC-GARCH for a master thesis in which I am investigating the co- movement of the Green bond and other markets pre and during the current economic crisis. Based on the signficant ARCH/GARCH ...
- 57
1
vote
1
answer
342
views
Implications of insignificant dccalpha and dccbeta for DCC-model used for co-movement analysis
I'm using a DCC-ARMA(1,0)-GARCH(1,1) model to investigate co-movement of the green bond market and other markets. The ARCH/GARCH parameters of the univariate ARMA(1,0)-GARCH(1,1)models are significant ...
- 57
2
votes
1
answer
2k
views
Interpretation of dccalpha and dccbeta in DCC-GARCH model
I've used DCC-ARMA(1,0) -GARCH(1,1) to model green bond co-movement with some other marekts. In the output, I get the parameters "dccalpha" and "dccbeta". However, I do not know ...
- 57
1
vote
0
answers
590
views
How can I implement a dynamic linear model in R?
Can someone explain me how to implement a dynamic linear model in R?
The concept is similar to a transfer function, which mathematically is defined as:
$$
y_t=c+w(B)x_t + N_t
$$
Where $y_t$ is the ...
2
votes
0
answers
633
views
A VECM in logs or a ARDL in the first difference of logs?
Suppose I have a number of time series that appear to have exponential growth at similar rates, with errors I believe to be generally proportional to the level of the variable. I believe that one of ...
- 3,187
0
votes
0
answers
632
views
Penalizing autoregressive models (with R packages)
Consider the class of linear or quasi-linear models that include an autoregressive term, such as autoregressive distributed lag models, ARIMA models, VAR and VECM models, and so forth. In general the ...
- 3,187
1
vote
1
answer
117
views
Dominance analysis in linear regressions with ARIMA errors
I have a question regarding dominance analysis in linear regressions with ARIMA errors. I am currently working with stress models for the banking industry. In certain cases, we are using dynamic ...
- 113
0
votes
0
answers
77
views
Intercept in a dynamic panel model
I have been taught that including fixed/random effects in a dynamic panel model yields inconsistent estimates when using OLS and hence motivates the usage of other estimation methods.
However, does ...
- 1,119
2
votes
0
answers
121
views
Skepticism about the claims of instrument variable validity/exclusion through a statistical test—the Arellano-Bond Test (cross-posted)
I am an applied researcher and occasionally come across papers that have panel data and that use dynamic models with both a fixed-effects term and lagged DV (or multiple autoregressive terms):
$y_{it} ...
- 280
4
votes
2
answers
4k
views
Choice between static and dynamic panel regression
I have a panel dataset with countries as individuals observed per year. My analysis concerns a macroeconomic study and as often happens in these cases (I would not be wrong but they are commonly ...
- 81
0
votes
0
answers
185
views
Is it possible to create a binary classifier from bayesian network?
I have a labeled data set consisting of longitudinal data and I would like to train a dynamic bayesian network. The output should be probability of the observation being 1 in a selected step given the ...
- 753
0
votes
0
answers
145
views
How can I get LSDV estimator of a two-way dynamic panel model?
I am now trying to explain a dynamic panel data model as follow:
$y_{it} = \alpha y_{i,t-1} + x_{it}'\beta + \mu_i + \lambda_t + \nu_{it}$
Here I want to compute its LSDV estimator $\tilde\beta$, ...
- 21
0
votes
0
answers
36
views
What are issues or best practices related to using fitted values from one model as predictors in a second regression forecast model?
I am creating two models, where the fitted values of one SARIMAX type model are used as an exogenous predictor for a second dynamic regression model. I want to understand what assumptions of the gauss ...
- 33
1
vote
0
answers
89
views
Can we use pooled ols on dynamic panel without individual fixed effect (but with group fixed effects) and no serial correlation in error
Is it correct that dynamic panel without individual fixed effect (but with group fixed effects), no serial correlation in error can be estimated consistently through pooled ols?
For example, suppose ...
- 111
0
votes
0
answers
87
views
Penalizing non-OLS models
Let’s consider some common linear time series models for which OLS does not usually yield unbiased coefficient estimates. These include ARIMA and ARIMAX models, regression models with ARIMA errors, ...
- 3,187
1
vote
1
answer
199
views
Product of independent beta distribution and gamma distribution
I'm reading Bayesian Forecasting and Dynamic Models by Mike West and Jeff Harrison. The following conclusion is about the variance discounting in dynamic linear regression model. On page 362, it says,
...
- 73
1
vote
1
answer
252
views
How to get first difference of count variable for poisson regression
Poisson regression using Panel data requires the dependent variable ($y_{it}$) to be a non-negative count variable. I need to take the first difference of the dependent variable to deal with reverse ...
- 143
1
vote
0
answers
35
views
Transfer Function in Dynamic Linear Model to Quantify Intervention Effect?
I have a time series consisting of 48 quarterly observations, relating to the area of land that was subject to development. I am trying to investigate whether a change in policy after 2011 caused an ...
- 31
1
vote
0
answers
43
views
How to build a function with the result of arima in R?
I use: arima(y, order = c(3,1,1) in R to get ARIMA(3,1,1), result as follows:
Call:
arima(x = y, order = c(3,1,1))
Coefficients:
...
- 11
0
votes
1
answer
590
views
Differences between Dynamic Regression Model and Intervention Model?
I am currently studying on dynamic regression and intervention model but I haven't have much resources on hand about the differentiating both of them. I understand that intervention model is a special ...
- 41
1
vote
0
answers
116
views
Why does the Anderson-Hsiao adjustment pick the twice-lagged first difference?
My understanding is that the Anderson-Hsiao adjustment, described here as an example, addresses concerns about potential or actual autocorrelation by taking a first difference of the dependent ...
- 143
2
votes
0
answers
123
views
Algorithm for dynamic linear regression with stochastic volatility?
Is there any paper or textbook on how to estimate dynamic linear regression model with stochastic volatility?
The observation equation and state equation,
$$Y_t = \beta_t'X_t + \epsilon_{t}$$
$$\...
- 73
0
votes
0
answers
119
views
Data preprocessing for dynamic linear regression
In DLM, what kind of preprocessing should be done before fitting the model?
$$Y_t = \beta_t'X_t+\epsilon_t$$
$$\beta_t = \beta_{t-1}+\eta_t$$
Should I transform both $Y$ and $X$ into stationary time ...
- 73
3
votes
0
answers
356
views
Standard errors with delta method
Trying to recreate other author's results. E.g. this paper. Introduction to the model is on page 10, while table with results is presented on page 13. Under the table there's a small note that SE were ...
- 604
1
vote
0
answers
215
views
How to run a Sargan-Hansen test?
I'm estimating a model with a lagged dependent variable and fixed effects for panel units. I understand that this can result in Nickell Bias but I didn't think it would be a big problem because there ...
- 51
1
vote
0
answers
159
views
Best practice for dynamic panel data estimation with multilevel structure in a $T \gg N$ setting
We plan to estimate a dynamic panel model with both, varying intercept and varying slopes. Further, we also want to include group-level predictors for the varying effects in second-stage regressions.
...
- 211
1
vote
1
answer
53
views
Training model vs model on whole data in time series forecasting in r
I have daily time series data of almost two years starting for Jan 2018 to Nov 2019 and need to forecast for next two months Dec and Jan.
My train data(Jan 2018-Aug 2019)is up to Aug 2019 and its ...
- 243
4
votes
1
answer
125
views
Linearisation of Kalman filter
Assume we have the following state-space model:
$$
z_{k} = \theta_{k} z_{k-1} + v_{k}\\
\theta_{k} = \phi \theta_{k-1} + w_{k},
$$
where $v_{k}$ and $w_{k}$ are independent and normal for all $k$. The ...
- 658
2
votes
0
answers
486
views
Can I estimate base sales in a Marketing Mix Model (MMM) with muddled promotional data?
I am building a marketing mix model (MMM) for an online casino, but they regularly run promotions and marketing campaigns that overlap. Trying to determine a baseline level of sales has been difficult....
- 21
2
votes
1
answer
48
views
Covariance in system with lagged reverse causality
Is there an easy way to find the covariance between $x_t$ and $\epsilon_t^1$ in a system like
$$y_{t} = \beta x_{t} + \epsilon^1_{t}$$
$$x_{t} = \alpha y_{t-1} + \epsilon^2_{t},$$
potentially under ...
- 5,559