Questions tagged [time-series]

statistical techniques for application to data whose observations concern an entity or phenomenon at different points in time.

Filter by
Sorted by
Tagged with
0
votes
0answers
25 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
186 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
362 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
54 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
votes
0answers
38 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
62 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
vote
0answers
24 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
84 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
votes
0answers
36 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
43 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
vote
1answer
54 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
votes
0answers
27 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 ...
4
votes
1answer
99 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
99 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 ...
2
votes
0answers
35 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
51 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 ...
2
votes
2answers
49 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
vote
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
vote
2answers
101 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
vote
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
votes
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 ...
1
vote
0answers
47 views

What would be the mean of a finite aggregation of AR(1) processes?

What would be the (expected) mean at each period $t$ of a (in)finite aggregation of $AR(1)$ processes generated by the same data generating process? How would the resulting plot look? For $i.i.d.$ ...
0
votes
0answers
14 views

how to adjust price data due to clock changes?

I'm trying to analyze the hourly price variation of the electricity market. However, because of clock changes, due to daylight saving time, we have a missing hour in March and an additional hour in ...
0
votes
1answer
56 views

How to determine covariant stationary values?

I am trying to determine the values for when this ARMA model is covariance stationary. I have the model: $z_t = a + Bz_{t-1} + u_t + u_{t-1}$ I have written it in terms of the lag operator: (1 - BL)...
1
vote
2answers
64 views

Why must the lag length of the autoregressive term in an ARDL model be determined separately?

I am estimating an autoregressive distributed lag model, and I've read that I must determine the lag length of my autoregressive term separately from the lag length of the other regressors in the ...
2
votes
2answers
98 views

Unit root testing in Eviews

I've plotted my data log(GDP) which displays an albeit small upward trend. However, after performing an ADF unit root test log(GDP) it suggests that I can reject H0 [that there is a unit root] at the ...
0
votes
2answers
46 views

Time series in monetary policy

I wanted to learn how time series analysis is used to study monetary policy/ money and banking data, such as how and which techniques are used to study which data, what kind of problems are studied ...
2
votes
1answer
35 views

Estimating a difference-in-differences with multiple time periods: why do margins results change when you simply change the base period?

My understanding of margins results is that they should not be sensitive to the base period chosen for a categorical time variable. However, I find that they are. ...
0
votes
0answers
11 views

Weakly Dependent Time Series | Common Error

I am watching a video, that mentions for the following time series: $x_t=\epsilon_t+\theta\epsilon_{t-1}$ $\textrm{Corr}(x_t,x_{t-1})≠0$ Then it mentions if we have anything greater then 1 such as $...
0
votes
2answers
34 views

causal time series analysis economics

I want to analyse the relationship between the level of globalization,and the level of income inequality between two specific countries. however, I'm quite lost as to which method is good to use (in ...
0
votes
0answers
100 views

Interpretation of Impulse Response Functions for VAR models using Log First Differences

I am exploring a VAR model with 9 variables but for simplicity let us consider a model with only two variables and one lag. The VAR model would look something like this: $$ y_t = \alpha_{11}y_{t-1} + \...
0
votes
1answer
38 views

Limit of random walk auto correlation function

Given the random walk process $y_{t}=y_{t-1}+e_{t}$, the auto correlation function is given by $corr(y_{t}, y_{t-h})=(\frac{t-h}{t})^{1/2}=(1-\frac{h}{t})^{1/2}$, which tends to 0 as t tends to ...
0
votes
0answers
120 views

Microeconometrics course vs time series

I am currently a graduate student in Operations Research and I would like to learn econometrics, as it is not a part of the core curriculum. I am comfortable with matrix algebra (many courses used ...
0
votes
0answers
35 views

Cointegration but no Granger causality

Suppose I have two variables - $y_t$ and $x_t$ - which are cointegrated. I believe that (i) $y_t$ responds to deviations from the long-run equilibrium, (ii) the long-run elasticity of $y_t$ with ...
1
vote
1answer
38 views

Forecasting quarterly EUR/USD exchange rate

My aim is to forecast the one-quarter ahead EUR/USD exchange rate. I have constructed a regression model with the following as explanatory variables: exchange rate in the previous quarter, EUR/USD ...
0
votes
1answer
26 views

Can you recursively forecast one variable using two variables?

My question is probably very elementary but I haven't been able to find an explanation of recursive forecasting that I fully understand. I've read a journal article that seemed to recursively ...
1
vote
2answers
31 views

Can you take the moving average of quarterly data of an explanatory variable in a regression to smoothen noise and get more accurate coefficients?

I'm trying to use acceleration of quarterly data on household debt (the difference in the difference in debt) in a regression on unemployment (only concerned with correlation) but quarterly data is ...
0
votes
0answers
29 views

Stock price and exchange rate is correlation, but VAR model order is zero

It is well known that Japanese stock price and exchange rate(USD/JPY) is correlation, So I built a VAR model in python about stock data(Tokyo stock price index) and exchange rate(USD/JPY) and I fitted ...
1
vote
0answers
8 views

Evaluating the impact of US federal grants

There are a number of challenges with evaluating the impact/effectiveness of federal grants in the U.S. In particular, it's easy to obtain a (somewhat comprehensive) record of transactions between ...
2
votes
1answer
55 views

Does it matter which is the dependent variable in regression of time series data?

I am testing for cointegration between the Real GDP per capita of England and France. I use a Dickey-Fuller test to test for stationarity and concluded that both of my series are non-stationary. So I ...
3
votes
1answer
326 views

Dealing with Missing Values in Diff-in-Diff Estimation

To preface this, I am asking this question on the Econ SE because I was made aware on Cross Validated that Difference in Difference estimation is quite an economics specific method. The picture above ...
0
votes
2answers
76 views

what can be the proxy variable for measure of product innovation?

My objective is to prove that international trade leads human capital formation which leads to economic growth. I am regressing GDP on multiple variables among which Human capital is one. According to ...
1
vote
0answers
17 views

GARCH data modeling

I am analyzing three time series returns for stocks, bonds and real estate, and have done prelimanary tests including Engle's ARCH test which came back as not rejecting the null hypothesis. IF there ...
2
votes
1answer
70 views

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_{...
2
votes
1answer
62 views

JNK and SPY price movements question

I am looking at the graph of JNK and SPY prices close prices since 2008. From 2008 to 2011, the two prices seem to move together. However, somewhere in the beginning of 2012, the prices all of a ...
0
votes
0answers
20 views

Regressing two unit root variables

I am supposed to explain the rate of customer defaults by some macroeconomic variables, such as unemployment, GDP growth etc. For simple linear regression, I have promising results: ...
0
votes
0answers
187 views

Should I include lags in an LLC unit root test?

I have panel data (N = 10, T = 20), which I intend to run a series of regressions on. I first want to see if my data are stationary in levels or in differences. To do this, I have been performing ...
0
votes
0answers
36 views

Stationarity of log industrial index and log CPI

I'm looking to estimate a VAR, one of the variables in this VAR is the log of industrial production, and another is the log of the consumer price index. Will I need to difference these to get ...
2
votes
1answer
22 views

Physical goods in a typical household

Estimating how much of physical goods a somehow typical person or household owns today (say in the Western world, compared to former times) is not so easy I guess, but there is one single number that ...
1
vote
0answers
37 views

Is there such a thing as resonance in economic underliers?

In physics the occurence of resonance is explained and widely understood in its linear form and subject to research in nonlinear resonance. Example for instance are resonant frequencies of objects. ...