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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(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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under what circumstances are regressors (x) correlated to the error term (u)?

suppose that Cov(Ui, Uj)=0 and Cov(Ui, X3i)≠0. What are some of the examples when one can expect a nonzero correlation between a regressor X3i and the error term Ui?
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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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What is an applicable instrument for my regression of demand for credit on interest rate?

I have a OLS regression for panel data with demand for credit as dependent and interest rate as independent. I'm worried about simultaneous causality and have decided on using an instrumental variable ...
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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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How to estimate Vector Autoregression during COVID-19?

Covid-19 has impacted macroeconomic forecasts. How can I avoid a vector-autoregression (VAR) model from under-estimating the forecasts? The series has undergone a massive drop from March 2020-May 2020....
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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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How do I fully decompose a time series into the influence of different factors/variables?

I am working with a dataset of monthly consumer prices, namely - year-over-year inflation. My goal is to achieve an exhaustive decomposition of an annual price change into the contribution of ...
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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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Which model is the most appropriate for my data?

I've been searching for the right model for several months, but i ended up with nothing untill now. That's why i'm here asking for help. My research purpose is to analyse the impact of rural programs ...
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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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How to statistically test relationship between two variables?

I am trying to investigate the stability of spread between two short-term interest rates by the example of 1M and 12M Euribor. I don't think only looking at correlations over time is statisically ...
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OLS regression on linear time series model

I am dealing with macro-economic data in EVIEWS11: new firms founded per year scaled by population ENT real gdp per capita Y stock market capitalisation scaled by population and in real terms MK ...
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How to find the log diff of data values on Excel? [closed]

I'm currently looking to run a MLR on GDP: quarter on quarter growth. I’ve been asked to find the log diff of the gdp, however I’m unaware on how to do this on Excel and how to account for negative ...
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VAR IRF for GPD with all GDP components

My question is twofold (hope it's ok). I want to estimate VAR model with the sole purpose of analysing the impulse response functions. I want to analyse the response of GDP to shock in exports and ...
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Why impulse responses are so weird in this exercise?

I ran my VAR model with inflation, real gdp, a proxy for fiscal policy and a policy indicator. I used the function externalinstrument in R and followed this ...
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How do I solve this system of equations?

I am doing something that is commmon practice in economics to uniquely identify matrices. After deriving 3 unrotated factors from PCA, I then want to rotate them to be able to interpret them in ...
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Johansen-Procedure Interpretation (ca.jo)

I am trying to run a Johansen-Procedure in a set of macroeconomic variables (GDP, credit outstanding and industrial production). I am working with them in level. How should I interpret the following ...
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Overview Standard Error Correction in Time Series / Panel Literature

In microeconometrics, the time component is usually short (meaning that $T$ is fixed in $t=1,\ldots,T$). Serial correlation is here usually just seen as a negligible issue affecting the standard ...
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How best to construct an indicator variable to capture the effects of an intervention? [closed]

How should one construct an indicator variable to properly capture the effects of an intervention? If an intervention like the 2008 bailout (TARP-Economic stimulus) is to get proper credit for the ...
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OLS, IV applied to basic macro model

I am preparing for my final in Econometrics but I am confused over a new problem I encountered. I think I have solved it but I am unsure whether I am not making any gross mistakes. This is the study ...
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First difference or seasonal difference in VAR/VECM

I have monthly data on house price, rental price, wage index and interest rates. I want to use VAR to produce impulse response function. Is there any reason why I should use first difference, x(t)/x(...
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Applying settlement and Regional fixed effects

I'm reading a paper by Gyöngyösi and Verner (2019), and noticed that the authors have included fixed effects at the settlement (seems to be akin to village/town) and at the region level, in a number ...
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How to analyse an impulse response function with more than 2 variables?

I am running an impulse response function in R, using the package vars. My data has 3 variables, the inflation (Brazilian CPI, or IPCA), the exchange rate and the output gap. My goal is to calculate ...
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Deseasonalize data AND deflate with CPI?

I have property return variables and economic variables that I am using in a VECM/VAR to generate Impulse Response Functions. I have deflated my data with CPI, but do I also have to deseasonalize the ...
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Can i use short time series data?

I want to run ols regression for time series data in R, but my data is short that is annual from 2000-2009. There are only 9 variables(2000-2009) and i collected data for inflation and exchange rate ...
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