Questions tagged [macroeconomics]
Macroeconomics is a general branch of economics which studies the behavior of larger economic entities like countries. Macroeconomists often analyze time series of country specific data (e.g. inflation, output, unemployment) to understand economic relationships. The application of statistics, specifically econometrics, to macroeconomic questions is called macroeconometrics.
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Using a test dataset with zero variation in the dependent variable for binary classification problem with panel data
For a university project, I am trying to come up with a probit model that estimates the probability of recession with at a given time using a panel dataset of various economic and financial indicators....
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Converting Monthly economic Data into daily data for Econometric analysis
I am trying to build an econometric model (VAR, VECM or regression) to predict daily interest rates based on daily financial data as well as monthly economic data.
I am unsure how to transition the ...
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Can we apply Fourier transform on non stationary data?
Hi, I'm trying to predict US inflation rate. The unit is in percentage change from a year ago. Would it be possible to use Fourier transform on the independent data to create a new feature, knowing ...
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ARDL model on monetary policy study on eviews
I am actually writing my master's theses on monetary policy trnasmission and I am doubting the results of my ARDL approach . I have 4 models ( 1 benchmark and 3 alternatives )
can someone take a look ...
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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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Does cointegration test of exogenous variable with Y variable make sense when doing ARIMAX/SARIMAX?
The cointegration test between two time series variable is generally relevant from my understanding when you are performing a regression model. In terms of ARIMA model the approach is straightforward ...
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How to keep time-varying but entity-invariant variables in a panel regression fixed effects model?
I am working with a panel dataset that spans 2000Q1 to 2020Q3 and captures quarterly capital flows to 35 different Emerging Market Economies (EMEs). Along with the capital flows data, I have several ...
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Multiple Linear Regression Predictions with Macroeconomic Indicators
We are given some commodity (steel, copper etc.) price predictions made by the following steps:
Finding the correlations between the commodity price data and macroeconomic indicators
Selecting a set ...
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How do I analyse the impact of various macroeconomic factors on 7 currency pairs?
I’m doing a Bachelor Thesis on “The Impact of Macroeconomic Factors On Currency Exchange Rates”. Narrowing down towards my methodology section, my professor advised me to analyse about 7 currency ...
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Propensity Score Matching and Regression
I'm currently writing a dissertation about the impact of IMF programs on economic growth, and as part of it I'm trying to control for selection bias.
I have my treatment variable which is whether a ...
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Partial autocorrelation significant at regular lag distance
I am trying to forecast inflation with a simple AR model.
I took the natural logarithm of the CPI and subtracted the 12th lag, thus obtaining a measure of inflation.
The PACF is significant at the ...
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How good are inflation expectations as a predictor on inflation?
I want to research inflation expectations and how well they predict inflation. I have found some past articles but none of them explain how to forecast inflation using inflation expectations. I have a ...
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How to compute the ergodic mean of a series?
In a paper, the authors say, "We can thus approximate welfare by computing the ergodic means of log consumption and log consumption growth from long simulations of the model.". They use the ...
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Write equations for $E[Y_{t+k}|X_t,Y_t]$ and $E[X_{t+k}|X_t,Y_t]$
I am working with a VAR and trying to understand the dynamics of it for forecasting. I am stuck trying to figure out the equations.
Currently, I am trying to generate conditional forecasts by ...
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Do I need to test for OLS assumptions(autocorrelation and normality) in cross sectional data with 2 time variant control variables?
My dataset consists of 950k unique loan observations over the period of 4 months. The institution is international, so it has some observations from different countries (not panel data). I am studying ...
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Choosing the best Time Series Decompositions technique for International Trade
I have monthly Export and Import of country by product groups and partners (countries). I want to analyze time series and decompose it into Trend, Seasonality and Remainder components.
My question is, ...
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Incorporating impulse responses while forecasting macro variables
I am forecasting a few macro variables such as inflation rate (INF), GDP, unemployment rate (UNRATE), federal funds rate (FFR) etc. Then, I imposed a 2 % upward shock on the federal funds rate, and ...
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Interpret the impulse response when define shocks in terms of variances of the residual of the equation
I’m trying to interpret the meaning of the shocks when they are written in terms of standard errors. I have constructed a multi-country Global Projections Model similar to IMF's model here. Suppose ...
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The meaning of Test Unit Roots: unanswerable and answerable questions
In the section 15.4 of Hamilton's book Time Series Analysis ( 15.4: The meaning of Test Unit Roots) the author says: Although it might be very interesting to know whether a time series has a unit root,...
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Non-stationary time series data and OLS regression (with controls)
I am using 2000-2020 quarterly data and want to test if an appreciation of the real exchange rate leads to a decrease in manufacturing output of a country. However, my data seems to be non-stationary ...
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(Undergrad looking for help) In logarithmic regression (log-log), what does it mean if your explanatory variable is already a percentage?
So I'm hoping to a regression of Human Development Index against some economic variables I think could affect it. Some types of aid per capita, education spending by government as a percentage of gdp, ...
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How do you interpret impulse response function values?
I'm trying to figure out how to interpret the output values of an impulse response function.
Consider a VAR model with 3 variables and 8 lags. The variables are, in order, gdp-gap, inflation ...
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What to do when kpss contradicts ADF?
I'm testing to see if Inflation has a unit root and if it has a drift and trend, just drift or no drift and trend. My results from the ADF test looks like this:
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Forecasting model with OLS
I am trying to estimate a model by using OLS (ordinary least squares) regression, I find that the default rate (my dependent variable) $y_t$ is non-stationary, therefore I take the difference to make ...
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SARIMA forecast of economic variables with shocks of COVID-19 [duplicate]
I am trying to fit a SARIMA model to a macroeconomic variable. However there is a huge drop in 2020-March due to Covid-19 and after 3 months the drop has been recovered. So the MAPE is very low. How ...
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Appropriate forecasting methods for only 20 observations [duplicate]
I am trying to forecast the regional GDP growth of our region in the next five years, I only have 20 observations in my data which is yearly, what forecasting model is appropriate?
I tried ARIMA in r ...
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Anything wrong with taking the log of an interest rate?
Suppose I am looking to forecast the 2 Year Treasury Bond rate with an ARIMA type model. The series is I(1) but its first difference does not look stationary due to non-constant variance. A general ...
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Covariance Matrix Estimation for the Generalized Method of Moments
I am solving and empirical exercise on the Generalized Method of Moments. It's a classical application/test of a famous model in Economics. There are 2 parameters $(\beta, \gamma)$ to be estimated ...
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Unexpected forecasts of unemployment by auto.arima
I am building a time series model on the historical monthly unemployment data. As my data starts from 1979, my first plot indicated that I should do two split analysis - all data (from 1978 to 2021 ...
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What kind of econometric models would be appropriate to determine the presence of a causal relationship?
I am conducting some econometric research on the impact of austerity on birth rates in the UK.
I would be using publicly available data from the UK government covering the number of births per year, ...
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VAR-Model with variables that have different degrees of integration?
I am estimating a VAR-model with three (anual) variables: GDP, Unemployment rate and Inflation. (57 observations)
Inflation and GDP are I(1), so I want to use them as growth rates in the model. But ...
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VECM coefficients and equations
I am building a macroeconomic model using VECM. I have a dataset divided into training and testing set and I am forecasting the future values of y. I performed all the testing and I want to get the ...
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Estimating stochastic volatility shock for TFP
I am trying to estimate a stochastic volatility shock for Total Factor Productivity (TFP) in a similar way to Fernandez-Villaverde and Rubio-Ramírez (2010) and Fernandez-Villaverde et al. (2011).
$$...
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Gross domestic spending on R&D data [closed]
I'm looking for data about R&D but I just found OECD data until 1981, so do you guys know where can I find data for R&D spending before 1981. Sorry if here it's not the place to ask for this
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How to add both long-term and short-term interest rates as variables for a GARCH model?
I was facing some difficulties with a model of mine. I want to look up how the portfolio reacts to interest rate changes and I would like to use a GARCH model. However, both the short-term and long-...
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How to check the consistency of OLS estimator in macroeconomic models
Problem:
We have a model $$C_t = a + b Y_t + e_t$$ and $$ Y_t = C_t + I_t$$ It's known that $Cov(I, e)$ is zero.
A student estimates the following model: $$C_t = a + b Y_t + e_t$$
Are the estimators $\...
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Database for Macroeconomic Time-series [closed]
I have decided to improve my well-being and in case being successful write a note about this and share it with my peers for free and try to help them improve there well-being as well. But on this road,...
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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 stationarity definition this means that the process has ...
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Calculating natural rate of unemployment
I have sample data on unemployment rate in a market and am looking to calculate the natural unemployment rate. The natural unemployment rate I obtained is constant over a time period, which is not a ...
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Using macroeconomic variables in Market Mix Model
I am building a market mix model from proprietary data to predict sales. I would like to include macroeconomic variables as well, such as unemployment rate and consumer confidence.
However, the ...
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Working with systems with Perfect Multicollinearity
I am working with a time-series dataset that is based on demand-supply dynamics with several variables. THe sample data for one time period is:
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How is the fraction of individuals with negative income handled in calculating the Gini coefficient in grouped data?
Much of the literature on theorizing and estimating the Gini coefficient $G$ is predicated upon the lower bound of the income distribution being $\$0$ (or whatever your unit of currency is); that is, ...
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When calculating the Gini coefficient for the US, how should the portion of the population which has not filed a return be incorporated?
The Gini coefficient $G$ is a commonly used measure of income distribution inequality, taking values from 0 (meaning every individual in the population has an identical income) to 1 (meaning a single ...
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Time Series Multivariate Forecasting
I am building a time series forecasting model in which I am considering the macroeconomic indicators as predictors.I wanted to understand 3 things
How do I generally go about feature selection for my ...
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Pros and cons of converting weekly to daily data
I am trying to forecast an economic variable called the "yield spread" in python. Among the variables in my dataset, two of them are measured on a weekly basis. These are:
unemployment ...
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ARIMA forecasts with autocorrelated residuals
I have a time series on consumer price index (CPI) and want to forecast inflation which is in my case the first difference of the log of CPI: ...
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VAR Model: Non-stationarity of variables
I am currently working on an empirical analysis in R. To give you some background information: I want to estimate a VAR-model to subsequently develop IRFs from it (using cholesky decomposition). My ...
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Granger causality over VECM (unknown possible problem in data)
I have data with 4 variables GDP, foreign debt, export (all in nominal values), and exchange rate.
Each of those are I(1) (the difference is stationary).
The four variables together are cointegrated ...
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Lagged values in a Lasso regression
While working on the statistics for my thesis, I became confused while building up my model.
I am currently working on a forecasting model with the use of a LASSO regression.
The model is build as ...
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Will simultaneity bias occur if I use VAR to test the linkages between monetary shocks, interest rates, and inflation?
I am writing an undergraduate paper and my goal is to investigate the liquidity effect. That is, I want to determine if expansions in monetary policy reduce interest rates.
Initially, I wanted to ...
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