# Tag Info

Accepted

### Stationarity in Time Series

First, recall that a stochastic process $\{ Y_t \}$ is weakly stationary if : $i)$ The first moment is time independent and finite, i.e. $E(Y_t) \equiv \mu < \infty$ $ii)$ The Variance is time ...
• 1,262

### $I(g)$-terminology

It's hard to tell without more context. But mostly sure it means "$Z_t$ is integrated of order $g$", i.e. $\Delta ^g Z_t=(1-d)^gZ_t$ (where $d$ is the lag operator) is stationary, in other ...
• 853

### Could you recommend a book or lecture notes about time series that is easy to understand?

The book I currently use for my time series class is "Time Series Analysis and Its Applications With R Examples" by Shumway and Stoffer, 4th edition. It's served me fine, and gives lots of ...
• 6,648
Accepted

### ARIMA - reason for + MA term

The MA terms are lagged errors (you don’t need to fetch them manually - for example in R you can use Arima function which does this for you and any program/language will have this basic function as ...
• 57.4k
Accepted

### Stationarity vs weak dependence

Weak stationarity and weak dependence are complementary conditions. A weakly stationary time series $y_t$ has an underlying statistical process which is time-invariant. This is characterised by three ...
• 597
Accepted

### Dickey Fuller Test

The problem in the unit root case is that the t-statistic does not follow a t-distribution, not even asymptotically. The issue lies in the distribution of the OLS estimator, $\hat{\phi}$. In the unit ...
• 1,262
Accepted

• 2,365

### Limit of random walk auto correlation function

Hi: The expression tends to 1.0. The intuition is that, as $t$ gets larger and larger, the $h$ lags that seperate the two processes become more and more negligible and the processes begin to look the ...
• 528

### Year Fixed Effects in a Dynamic OLS Regression with Cointegrated Variables

No in pure time series we generally don't use fixed effects. If you have data on lets say monthly frequency you could include dummies for months in general, e.g. having February, March, April ... ...
• 57.4k

### How much can we trust macroeconometric analysis?

I do not think that macroeconomic analysis would be 'less trust worthy'. In the same ways as you can solve the issue of omitted variables and reverse causality in microeconomics you can do it ...
• 57.4k

### Regressing (Very) Smooth Time Series

One thing to consider, is that it looks like you may have a unit root, though not necessarily. An example of a unit root would be the stochastic process $y_k=y_{k−1}+\epsilon_{k−1}$, where the error ...
• 6,238