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I am testing a variety of models to produce 1-month ahead predictions of US Recessions. To benchmark these models, I want to build a naive recession model. My first thought was to use the current state of the recession variable to predict the next state of the recession variable:

library(quantmod)
getSymbols('USREC',src='FRED') 
library(caret)
confusionMatrix(Lag(USREC),USREC,positive = '1')

As you can see, this forecast is very accurate. However, recessions tend to be back-dated so the naive model occasionally has information from the future: it knows a recession has started before the NBER has made an official announcement!

One idea I had was to build a simple glm model relating GDP to recessions. This method still uses future information (and the quarterly numbers have to be interpolated to monthly ones):

#Load Data
getSymbols('GDPC1',src='FRED') 
GDPC1 <- diff(log(GDPC1))
Data <- cbind(USREC,GDPC1)

#Fill NA's in GDP
Data$GDPC1 <- ifelse(is.na(Data$GDPC1),Lag(Data$GDPC1,1),Data$GDPC1)
Data$GDPC1 <- ifelse(is.na(Data$GDPC1),Lag(Data$GDPC1,1),Data$GDPC1)
Data <- na.omit(Data)

#Build Model
model <- glm(USREC~GDPC1,family=binomial(link = "logit"),Data)
forecast <- predict(model,Data)
confusionMatrix(ifelse(forecast>.5,1,0),Data$USREC,positive = '1')

On the other hand, this model is a little less accurate, and may be useful as a benchmark, despite it's use of some future information

Are there any other simple recession models I could use as benchmarks?

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2 Answers 2

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Use a logistic model predicting the probability of a recession using independent variables such as the slope of the yield curve, trailing stock market returns, short-interest rate, and credit spreads.

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  • $\begingroup$ That's what I did in my example. model <- glm(USREC~GDPC1,family=binomial(link = "logit"),Data). I'll add the yield curve, stock market returns, interest rates, and credit spreads as variables $\endgroup$
    – Zach
    Commented Sep 12, 2011 at 15:22
  • $\begingroup$ There is a well-known economic factor model called the BIRR model : www.birr.com/BIRR_Risk_Model.pdf . They are not forecasting recession (they focus on the equity risk premia) however you might find their approach instructive. Several of the variables I suggested are from that model. $\endgroup$
    – Ram Ahluwalia
    Commented Sep 12, 2011 at 16:07
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In the end, I decided the best way to do this is to use the recession announcement dates to construct a recession variable that reflects what was known at the time. A commentator on my blog was kind enough to go back and construct the data series, which is available as an excel file and as a csv file.

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