Questions tagged [time-series]
statistical techniques for application to data whose observations concern an entity or phenomenon at different points in time.
248
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Data analysis with GARCH modeling
I'm currently analyzing the relationship between stock, bonds, and real estate returns in Germany. I've gathered my data and am planning on estimating this equation:
$\sigma_t = \beta_0 + \beta_1 R_{...
CommunityBot
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SVAR: proof of the $(K^2-K)/2$ restrictions and identifiability?
I'm currently using Structural vector autoregressive models by Kevin Kotzé to learn Vector Autoregression. One of the points that it makes is the following:
the number of restrictions that we need to ...
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Why does the sign on the variable changes with the lag while running ARDL model?
The dependent variable of the model is mortality rate, while independent variable is mean: Mean year of schooling, and GDP for the Gross domestic product, percentage change. While they are all either ...
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Why given real and manually deflated series are not same in FRED?
when I deflate a series (for specific example, take M1 (M1SL) series from FRED) by CPI, it is not exactly the same as the one the that FRED provides i.e. M1REAL. It seems like M1REAL is a scaled up ...
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Analysis of seasonal adjustments and moving averages: seeking guidance
I'm looking to seasonally adjust the price data I have using a moving average with a 12-month window size. As window 12 is being used, the first 11 values in the 'Oil_adjusted' column are being filled ...
CommunityBot
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On assumptions of local projection method
It is well known that Jorda(2005) proposed the following model called local projection:
$$y_{t+h} - y_{t-1} = \beta_h shock_{t} + \gamma_h ctr_{t-1} + \epsilon_{t,h}, h = 0,1,2,\dots,H.$$
I am trying ...
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Structural breaks in price time series: when to test?
I am investigating the price transmission between two inflation indices within the same sector but at different stages of processing. For example, I might be looking at the relationship between raw ...
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Modelling a likely unit root process with ARMA? HAC standard errors in python time series packages?
I am working on a project to forecast Canada's GDP. One of the exogenous variables for my ARDL model that I consider is the treasury spread. By plotting its ACF and PACF, I notice that it can be ...
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General conditions in which dynamic panel effects are bounded by OLS and FE models?
Typically under the model that looks like this:
$$ y_{it} = \rho y_{it-1} + u_i + e_{it} = \rho y_{it-1} + v_{it} $$
Define the OLS estimator as the estimator for $\rho$ that estimates the following ...
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How to assess the quality of a forecast?
Let's say I have a time series model (VAR model for example). How can I know that my forecast is good ? I could use the R2 but is there something else? I also know I could just use in sample ...
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For a diff and diff should I use stationary series or non stationary?
I am trying to do a diff and diff analysis on the impact of QE for US (treatment) and Canada (control). What kind of series should I use and what dummys should I include?
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Simplest explanation of “Why isn’t an asset that produces recurring reliable dividends worth infinite money?”
Let’s say there exists an asset that is known to produce $1 of liquid value annually, indefinitely.
In practice, this asset is worth a finite amount of money. However, to a naive intuition one could ...
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Good practice in time series tests with different start/end dates
I am testing purchasing power parity on monthly data, in a sample of about 70 to 200 countries depending on which price index / currency pair is used. Would it be considered bad practice to use ...
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How to interpret detrended data in GDP modelling?
So I detrend 5 variables that I fit in an Almon model to predict GDP. The problem is beforehand I detrend them and their values become much smaller. Also, I detrend the GDP itself and it becomes ...
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Why is GDP a random variable?
I have seen in time series models that GDP is considered a random variable. At first, I found this troubling because I could not see any random process underlying the measurement. However, the ...
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How to Find the Relationship Between Variables in Time-Series Data?
I would like to find the relationship between two variables (spending and earning) in time-series data and I am wondering if VAR would be a good way to approach this? If not, which approach(es) would ...
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What should I do before an OLS regression and Johansen cointegration test with time series data?
I have to make a regression with real exports as the dependent and then an aggregated GDP income variable and the real effective exchange rate as independent variables. My variables are time series (...
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What kind of econometric analysis can be used on Indian domestic petroleum sales 2008-2018? [closed]
I have data for sales of petroleum products across different states in India of both public sector and private sector companies for 10 years.
Number of years: 2008 to 2018 monthly data (10 years)
...
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Help with Simulating a Time Series Process in R
I'm having difficulty expressing the following process in its most reduced form. Every time I try to simulate it with the arima.sim function, I end up with a non-stationary AR part that cannot be ...
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Stationarity in Time Series
Could you illustrate why a random walk process without a constant term exhibits stationarity in its first moment but not in the second?
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Dickey Fuller Test
Consider the following AR(1) model:
\begin{equation}
Y_t = \alpha + \phi Y_{t-1} + \varepsilon_t
\end{equation}
I want to test the existence of a unit root for $Y_t$, and thus, I intend to implement a ...
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Self-selection problem can be solved in panel data analysis?
Assume that there are two variables $x$ and $y$ and they both have trend.
For example,
(case 1) During covid-19, government spending($x$) and inflation($y$) are both increased
(case 2) A productive ...
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Normalization for model comparisons
I have a time series applying the Markov Switching model, which is estimated in about 15 different versions. One or two of the time series had to be normalized in order to converge. That is 1-2 out of ...
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Forecasting and Structural Breaks
Let's say I am using walkforward evaluation for forecasting a certain time series with ARIMA and I want to test for structural breaks. And then I detect structural breaks. How can I use this ...
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Is there a good catalogue of time serries available from the Federal government?
I have two closely related questions that I will present here in separate postings. It seems that lately I have spent a great deal of time looking for particular time series that may or may not exist. ...
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Granger-Sims causality and subtle differences
For a bivariate process $(\textbf{X},\textbf{Y})=( (X_t, Y_t)^\top, t\in\mathbb{Z})$, we say that the process $\textbf{X}$ Sims-causes the process $\textbf{Y}$ (notation $\textbf{X}\overset{Sims}{\to}...
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can i use a variable for ardl testing
i have done unit root testing on my time series variable using both the adf and pp test. at level difference my variables all appeared non stationary.i used the option 'trend' and speratley 'drift' on ...
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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 ...
CommunityBot
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How to formulate intra-day return?
So I have time series data on the bitcoin price. For each day there is an open price and a close price. In many papers they calculae the return like this:
$$ R_t = \Delta P / P_{t-1} = ln(P_t/P_{t-1})...
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Critical Value for Chow Test
What are the degrees of freedom for the F-distribution used to find critical values for the Chow Test?
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Does discount rate and cost of capital mean the same thing to compute levelised cost of energy (LCOE)?
I came to understand that cost of capital and discount rate are two different parameters, although they are also used ...
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OLS estimation of AR and BLUE
Is it valid to apply OLS to the AR process?I learn that there exist correlation between explanatory variables and error term in AR model. I'm wondering how can show that $E(u_t|1,y_1,y_2,...,y_{t-1})\...
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Which sample size would be best to investigate effects of War in Ukraine on volatility of stock prices using GARCH models?
I am planning to investigate the effect of the war in Ukraine on the stock market prices by including in a GARCH model a dummy identifying the burst of the war.
I am wondering if I should strictly use ...
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confidence interval for standard deviation of bitcoin price
I am actually doing some research on bitcoin for my bachelor thesis. I have daily data on the price of bitcoin from here. I calculated with python:
...
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How do I set up a staggered difference-in-differences design in R?
I have data which looks like this:
...
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Regression OLS estimator with $x_t=1/t$
I found some questions in a book and wanted to train for my upcoming exam (expect to see some more posts from me idk), anyhow this is the question.
To solve point A I rewrote the whole equation in ...
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Why don't Time Series books talk about exogeneity like in classical linear regression models?
Consider the following linear regression:
$$y_t = \beta_0 + \beta_1 x_{t} + u_t$$
Typically, we need to assume (assuming a random sample):
\begin{equation}\label{I}\tag{I}
E[u_t]=0, \quad cov(u_t ,x_t)...
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Time series question from book (ma)
I'm trying to understand this subject and I'm stuck in a question found in a book.
I understand white noise characterization, but I'm having some problems with this... maybe it's too much theory? I ...
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Applications of a certain type of stochastic processes in macroeconomic, macroeconometric or finance
A compound Poisson random vector $Y$ is well defined in this site in wikipidia.
Nothing prevents me from compound strictly stationary stochastic processes instead of compound random vectors. The ...
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Comparison of two AR(1) regression models (lead in dependent vs lag in dependent variable)
What is the difference between these time series AR(1) regression models (lead in the dependent vs lag in the dependent variable)?
$$\begin{align}y_t = constant + \alpha y_{t-1} + error \tag{1}\label{...
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Include 'year' as an independent variable to deal with autocorrelation?
I'm working on an econometrics project for which I'm trying to study the impact of factors such as p.c. GDP growth, exports, inflation and interest rate on the debt-to-GDP ratio of a country, for 4 ...
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The difference of a difference for a control variable in a regression?
I am conducting a time series analysis. My dependent variable is income inequality, which has been logged and then differenced. In other words, my Y variable is now the difference in log income ...
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Machine learning and Inflation forecasting
Is machine learning a good tool to use in order to forecast inflation for the short term (next 2 - 3 years on a monthly or quarterly basis)?
I want to be able to forecast inflation for Canada for the ...
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Deriving ADF unit root test form for the time series with quadratic deterministic trend
I have the following time series process $y_t $
$$\Delta y_t = \delta + \gamma t + \epsilon_t$$
where $e_t$ is white noise process with the variance of $\sigma^2$.
I guess that whereas $\Delta y_t$ is ...
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Application of Maximum Likelihood estimation (MLE) to the Generalized Least Square (GLS) model
I have the following regression
$$y = X\beta +u$$
where $y$ and $u$ are $(n\times 1)$ and $X$ is a fixed $(n \times k)$ matrix with full column rank and $\beta$ is an unknown $(k\times 1)$ vector of ...
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The effect of stationarity of forecasting
If all that matters in forecasting is getting an accurate forecast then why is using non stationary data a problem. Say you use non stationary data to create a forecast that performs well in a pseudo ...
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Which variable keep/get rid in a time series model?
Let s say I have a big VAR model with many variables. Then I run the model. How can I know which variables I should keep or get rid of if I want to ameliorate my model ?
What if my model has so many ...
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can someone help to interpret ACF and PACF graph?
can someone help to interpret ACF and PACF graph?
in the graphs, I don't see any decay. am I right about that assumption
other than that what can I comment about both?
the data plotted is squared ...
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Cholesky Identification in Structural VAR
Can you suggest me a framework in macroeconomics or finance where identification of a Structural VAR model through Cholesky ordering is still considered credible (in your opinion)? I'm looking for a ...
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Is there granger causality that can be applied to panel data with structural breaks?
I have panel data containing various macroeconomic variables (for example: interest rate, output, unemployment).
I would like to run a Granger causality test on some of them, but there are structural ...
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