Questions tagged [dynamic-regression]

Dynamic regression is a type of regression, where one of the independent variables is a lagged dependent variable.

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What does mean to have the number of used observations greater than the sample size in the Generalized Method of Moments(GMM) result?

I specified my model as follow: The result below gives a value of the Sargan test around 0.3, which is good according to Roodman. However, the number of used observations is greater than the sample ...
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Dynamic panel with binary outcome

Suppose I have a dynamic panel data model with unobserved heterogeneity. $$ y_{it} = \alpha y_{1,t-1} + \boldsymbol{x'_{it}\beta} + \epsilon_{it} $$ $$ \epsilon_{it} = \mu_{i} + \upsilon_{it} $$ I ...
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29 views

Pooling dynamic panel models (dpm) with mice::pool in r

I have multiply imputed panel datasets that I have constructed with amelia. I put them in a list and constructed a corresponding list of ...
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1answer
16 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 ...
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20 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 ...
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1answer
102 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 ...
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9 views

Investigating lagged effects of an independent variable on a replicated dependent variable

I have data from repeated observations of ~60 independent replicates over 20 consecutive years, along with an environmental index. Let's say these data are the annual quantity of apples produced by 60 ...
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57 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 ...
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11 views

Regression of y=f(x) where y and x are both AR(1) processes: GLS, ARIMA, ARIMAX?

I’ve been working with some biological productivity data ($y$). There is good theoretical reason to think that productivity follows an AR(1) process given the hold over from one time to the next of ...
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50 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 ...
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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 ...
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Short-run effects in a dynamic model with combined variables?

(The models I estimate are actually dynamic panel models. For simplicity of expositon, I abstract from including cross-sectional indexing). The original model that I wished to consider is: $$y_{t}= \...
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1answer
53 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 ...
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23 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 ...
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33 views

Specify dynamic structure in a panel regression

I am recently approaching the dynamic panel models proposed by Arellano-Bond (1991), Arellano-Bover (1995) and Blundell-Bond (1998), in particular I am trying to understand the hypotheses underlying ...
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55 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} ...
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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 ...
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45 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 ...
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Dynamic panel model assessing temporal relationships with 2 conditions with varying timepoints

I want to perform a dynamic panel model to investigate the temporal relationship between 2 variables (working mechanism and outcome) using R package dpm (following the method of Allison, Williams, and ...
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36 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 $\tilde\beta$, ...
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23 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 ...
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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 ...
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36 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, ...
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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, ...
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1answer
118 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 ...
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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 ...
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21 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: ...
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242 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 ...
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50 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 ...
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68 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, $$Y_t = \beta_t'X_t + \epsilon_{t}$$ $$\...
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51 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 ...
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118 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 ...
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49 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 ...
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81 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. ...
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1answer
34 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 ...
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1answer
110 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 ...
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270 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....
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39 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 ...
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42 views

Auto.arima coefficients with exogeneous variables

I have the following output from the auto.arima function with specified xreg: ...
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156 views

Calculating standard errors for long-run (cumulative) multiplier in a Distributed Lag model

I have a distributed lag model of the form: lm(wellbeing ~ temperature + temperature_lag1 + temperature_lag2 + time + individual, df) where I'm interested in ...
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110 views

Dynamic regression, models with coefficients = 0 chosen as top models

I am running auto.arima on part of a time series (training data) using all possible combinations for several external regressors. I then choose the top 5 models according to fit to testing data using ...
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465 views

Using Decomposition to Extrapolate seasonality, cycle and trends of predictors

I'm creating a dynamic regression model in which macroeconomic indicators are predictors/features in the model. I need to forecast these features n-steps into the future. I am planning to decompose ...
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788 views

Lagged variables in multilevel models

Is it okay to use lagged dependent variables as predictors in multilevel models? i.e. If there are $j$ groups of $i$ individuals each measured $t$ times, to model $$ y_{ij} = \beta_{0j} + y^{-1}_{ij} ...
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Dynamic poisson-time series regression

Basically, my question is similar to Time series dynamic poisson regression, yet I didn't get any clue by its answer. I'm modeling dengue incidents with GLM (poisson regression; because the response ...
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1answer
412 views

Transfer Function Clarification

I'm seeking a little clarification on the specific application of transfer functions for time series. I've followed the Box-Jenkins approach for selecting potential exogenous predictors... using R's ...
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Regressing across multiple different time series using exogenous variables?

To make this situation clear, I'll use a somewhat silly, but conceptually simple example. Imagine I record teams of movers carrying furniture down the block. I measure the furniture's position/speed ...
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184 views

Multilevel dynamic linear models in R

I am interested in fitting a multilevel bayesian structural time series with a hierarchical structure of the dynamic regression coefficients. The reason I want to do this is is that I have a number of ...
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55 views

Modelling dynamic panel data

I have a question about a dynamic panel data model. Consider the panel data model: $y_{it} = \alpha_i + x'_{it}\beta + \delta y_{i,t-1} + \epsilon_{it}$. This cannot be estimated because $\alpha_i$ is ...
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Time series model for demand forecasting?

I have a time series $Y_t$ (example:university applications received in a certain month) which I want to forecast. I have another time series $X_t$ and I know that $Y_t$ is related to past lags of $...
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1answer
1k views

Short Run vs Long Run Effect in Dynamic Panel Regressions

This video differentiates between short run and long run effects of an independent variable in dynamic panel regression (from 19:25 to 20:50). Firstly, I would like to know when and why do we ...