Questions tagged [time-series]
statistical techniques for application to data whose observations concern an entity or phenomenon at different points in time.
181
questions
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0answers
32 views
Detrending multiplicative model
I have a GDP quarterly series and IND.P monthly series, which I need to detrend. I am following Bernanke et al. paper from 1995 and the way they do it is:
...
1
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1answer
21 views
What does “sample period” in this case mean?
Dasgupta,2019 documented that
the treated group comprises all firms that are headquartered in
countries that have passed a leniency law by year t. The control group
comprises firms in countries that ...
0
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0answers
29 views
looking for detailed case studies on how high inflation was dealt with, with all pertinent objective facts [closed]
i am looking for case studies on how high inflation was dealt with in different countries.
if anyone can post whatever detailed and objective fact compilations (facts as i detail further down) Sources ...
0
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1answer
31 views
How to handle the missing values' issue of newly listed stocks?
I am trying to test some asset pricing models on 10 portfolios for the period of 2010-2020. The problem is that three of these portfolios included stocks that are newly listed in 2017 and 2018, so I ...
1
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2answers
48 views
Examples of the use of Vector Autoregressive Models
I am self-learning Vector Autoregressive Models currently, and have practiced on a few datasets. But I wanted to read some actual research papers that use VAR, so that I get an idea of the level of ...
1
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0answers
21 views
What is the importance of moving seasonality in seasonal adjustment?
Both Stable and Moving Seasonality are computed in Sliding span test (or D8 F-Stat test) and M7 statistics. But what is the purpose of finding out the presence of moving seasonality in seasonal ...
1
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0answers
25 views
Modelling GDP growth rates with an AR(1) process
I am trying to model the growth rates of real output per worker. I read that GDP growth rates are often assumed to be stationary and are modelled using an AR(1) process, so I took logs and then took ...
1
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0answers
25 views
Stationarity of variables for Local Projections
Should we care about the stationarity of the time series when doing Local Projections?
In his website Jorda (the author of Local Projections method) provides a code for doing local projections : https:...
0
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1answer
17 views
Nominal Values or Real Value & stationary
I'm going to estimate a time series regression which has consumption as a dependent variable.
My data source give it in nominal form and unfortunately there are no other sources. It is
Question :
Can ...
1
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0answers
29 views
Local Projections: lags and horizon
I would like to know what to consider when deciding about lag (p) and horizon (h) to estimate impulse responses with local projections. Jorda (2005) and Plagborg-Moller & Wolf (2019) talk about ...
1
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1answer
79 views
Converting monthly data to quarterly
I have monthly shock series, which I want to convert to quarterly form. I have seen several methods like taking average of 3 months or summing 3 months for making a quarter. I would like to know how I ...
0
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0answers
20 views
rebasing an index with inconsistent ratios between old and new data points?
I have a question about rebasing indices, hoping someone might be able to help.
I'm working with two sets of index data for residential property prices from the Australian Bureau of Statistics. the ...
3
votes
0answers
19 views
Extract residuals from Uhlig's rejection method - Lag selection
I wanna determine the number of lags for a Baysian VAR/FAVAR model, which I implement based on R's VARsignR package. To compute the AIC/BIC I'd need the residuals of the model estimation. How can I ...
2
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1answer
32 views
Regressing (Very) Smooth Time Series
What are the possible problems/issues of regressing smooth time series with almost no fluctuation?
Here is a specific example.
Is there anything I have to pay attention to when interpreting ...
2
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0answers
26 views
Do you know how to compute the IRF of a GARCH (1,1)
We have the following model (GARCH (1,1) )
$y_t=\sigma_t\epsilon_t$
$\sigma_t^2 = \omega + \beta*\sigma_{t-1}^2 + \gamma*y_{t-1}^2$
Note that we can rewrite the latter as:
$\sigma_t^2=\frac{\omega}{1-\...
4
votes
1answer
72 views
Should Prices (or Price Indices) be modelled with deterministic trend?
I always face a dilemma on whether to assume prices to have a time trend or not while modelling. It is also partly a statistics problem. Let me explain. Assume I have time series, $y_t$ of price of a ...
3
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1answer
251 views
Stationarity vs weak dependence
I am doing an undergraduate course in econometrics where we are using the text Introduction to Econometrics by Dougherty. While going through time series, it was mentioned that one of the necessary ...
0
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0answers
29 views
Could a time series be a pooled OLS?
Hello to everyone on the forum,
I am currently working with intraday electricity price data. In the electricity market each hour is considered as a different product, because the demand and production ...
0
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0answers
25 views
Comparison of coefficients in log(y_t) and log(y_t/y_0) LHS specifications in LP-IV
I would have a question related to econometrics. Likely not all the details are needed, but please bear with me.
My goal is to use local projection with an instrument to find out the response of an ...
0
votes
1answer
25 views
Stationarity, ADF/KPSS, Autocorrelation and Heteroscedastiy
i have a time series which is not stationary due to ADF/KPSS test, but is is in its first difference. So ADF and KPSS tell me it is starionary so it has a constant mean/variance/autocorrelation. But i ...
1
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0answers
23 views
Does GMM have any assumptions that you can't test empirically (and must instead argue qualitatively for)?
My understanding is that you can empirically test some of the main assumptions required for using a GMM estimator. Namely, I understand that you can test over-identifying restrictions with Hansen's J ...
0
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1answer
34 views
Variance in the Context of a AR (1) Model
I wondered if someone could help me in terms of the required algebraic steps from expressions (3) - (4), for the the moving average representation of the AR (1) below?
Would be appreciated.
$$y_t=a +\...
1
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1answer
70 views
Recursive Substitution in Time Series
Would appreciate some guidance on a matter of recursive substitution, where we have the AR model:
$$y_t = \alpha +\theta_1y_{t-1}+ u_t$$
And
$$E(y_t)= \mu_t$$
Where:
$$\mu_t = (1+\theta_1 + \theta_1^2+...
0
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0answers
44 views
What type of econometrics is practised most?
This might sound like a weird question, but what type of econometrics is most common in academia and / or the private sector?
Here I am thinking about time series econometrics (Bayesian and ...
1
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1answer
19 views
How does using HP filter allows us to estimate long-run values for variables such as output and unemployement?
I'm reading the paper "Okun's Law: Fit at 50?" written by Laurence Ball, Daniel Leigh and Prakash Loungani.
In it, in order to estimate Okun's Law in its level form, they use the HP filter ...
1
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1answer
31 views
Should one remove trend from time series before testing for cointegration?
Should one remove trend from time-series before testing for cointegration? I guess no, but I couldn't find any answers yet.
Also is it necessary to remove trend before estimating a VAR model if the ...
0
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0answers
39 views
Deconvolution in economics
Here it says
In mathematics, deconvolution is an algorithm-based process used to
enhance signals from recorded data. Where the recorded data can be
modeled as a pure signal that is distorted by a ...
0
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0answers
18 views
Is it okay to difference data with different time intervals?
I have a question that is from an old project and that I want to clarify purely for future research.
The question is, if you have a time-series that occurs at intermittent intervals, say once ever 4, ...
3
votes
1answer
179 views
ARIMA - reason for + MA term
I have 2 questions regarding ARIMA.
1st: How do we get the MA component - the et's (as we want to regress yt on lagged yt and also et and lagged et's)? If I want to regress yt on lagged yt's, I have ...
2
votes
4answers
317 views
Could you recommend a book or lecture notes about time series that is easy to understand?
What are some time series texts that you would recommend to start studying? Some easy textbooks/lecture notes or step by step for undergraduate level.
I'm not so good at math/statistics.
0
votes
1answer
51 views
GDP per Capita in Panel Data: Must the base year be the same for all cross-sections?
I'm trying to run a small project using time series in panel data. One of the variables used is the GDP per capita for a few countries (the countries are the cross-sections). Is there a problem if the ...
0
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0answers
25 views
graph of dependent variable after years of restructuring in panel data
i'm not very able to use stata. For my thesis, I have a panel data(1970-2017) for different countries and a lot of variables.
In this dataset, there is a dummy (dhairendH) that is equal to one in the ...
1
vote
1answer
56 views
Time Series Analysis - What lag level is appropriate?
In my undergraduate econometrics class we were taught the basics of time series analysis. We were basically told to use a model with a one period time lag (lag = 1). However, I wonder that there must ...
1
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0answers
23 views
Intuitive/Practical meaning of non-stationarity of GDP Data
As i just read in a time series book that a particular GDP data under consideration is non-stationary verified through various tests. From non-stationarity definition this means that the process has ...
1
vote
1answer
81 views
How much can we trust macroeconometric analysis?
I am a student of economics in my masters and I have learned quite a lot about microeconometrics (I mean mainly quasi-experimental methods / causality determination). Here my current understanding is ...
0
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0answers
35 views
Time series Econometrics demonstration
Hey there! Can anyone help me with this? I am able to arrive to expression (3) from (2) by using the lagged variable and make the variation from $Y_t$ and then divide to the right such that $\beta_0 = ...
2
votes
1answer
31 views
Difference between long run coefficient and non stochastic steady state coefficient ARDL model
I am a little bit confused on the definition of long run equilibrium coefficient. Suppose I have an ARDL model as:
$y_t = \rho_1 y_{t-1} + \rho_2 y_{t-2} + \beta_1x_{t-1} + \beta_2x_{t-2} $
The steady ...
1
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1answer
36 views
How to test for invertibility in ARCH family models?
I hope everyone is doing well.
Citing Enders (2014) in the book Applied Econometric Time Series: "the Box–Jenkins approach also necessitates that the model be invertible" while discussing ...
2
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0answers
23 views
How to choose information criterion?
In time series analysis, it is often important to determine the optimum number of lags in order to remove serial correlation. For example, in VAR, Dickey-Fuller unit-root test or Granger causality ...
3
votes
1answer
87 views
Skepticism about the claims of instrument variable validity/exclusion through a statistical test—the Arellano-Bond Test
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} ...
4
votes
2answers
63 views
Year Fixed Effects in a Dynamic OLS Regression with Cointegrated Variables
I am estimating a dynamic OLS model since I have variables that are non-stationary, but cointegrated. In addition, the data is a standard time-series (i.e. one observation per one time period) so ...
0
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0answers
20 views
Interpretation of largest inverse root in a stationary time series
Let's consider a stationary time series that can be modelled with an AR(p). I know that the cumulative effect of a shock is given by$$ \frac{1}{1- \sum^p \theta_i}, $$ where $\theta$ are the ...
2
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0answers
30 views
On Cointegration with Structural Breaks
I am slightly confused about the requirements necessary to conduct a cointegration test with structural breaks such as the Gregory-Hansen test.
Suppose I have two I(1) variables.
Variable 1 follows a ...
3
votes
1answer
48 views
Can You Use Filtered Variables in OLS?
I have two variables that are non-stationary and contain stochastic trends. I used the Hamilton filter( an improvement over the HP filter) to remove the trend and isolate the cyclical component. My ...
1
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2answers
46 views
How do I predict Macroeconomic indicators?Or are there any free resources where I can get the predicted values?
I am building a time series forecasting model in which I am considering the macroeconomic indicators as predictors.I wanted to ask 2 things
How do I get the future values?I have seen trading ...
1
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1answer
28 views
markov-switching model and stationarity [closed]
To test the structural breaks and to perform markov-switching model in time series data, should i have stationary data.
Thank you in advance.
1
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2answers
80 views
Stationarity of cyclical economic data
I'm having trouble understanding how macroeconomic or industry data could be made stationary if there's only a limited length of time series available (e.g. 2012-2019) and I have a time series that ...
1
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0answers
10 views
Correcting high AR(1) coefficients in dynamic Gordon model
I have just finished my thesis on a heterogeneous dividend expectations model applied to the COVID-19 crisis. However after receiving some feedback there is one last issue I want to resolve. I'm using ...
0
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1answer
21 views
Does analysis at two points in time count as 'longitudinal'?
According to whatever norms and expectations exist in the econometrics literature - if an analysis looks at two points in time can this be described as longitudinal, or would more time slices ...
0
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0answers
32 views
Using ML to estimate demand function
Say, I am looking to estimate the demand curve for rental of a real estate property. The demand varies depending on time of the year, location, economic and demographic variables.
I'd like to ...
