Financial and Real Sector Leading Indicators of Recessions in Brazil Using Probabilistic Models

Oliveira, Fernando Nascimento de

doi:10.5935/0034-7140.20160017

Fernando Nascimento de Oliveira

Banco Central do Brasil and Ibmec/RJ. Email: fernando.nascimento@bcb.gov.br

Figure B-1
Recession probabilities with indexes of equal weighted average of forecast of best ROC models from 1 to 8 quarters (Index1, Index2).

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Figure B-2
Recession probabilities with indexes of equal weighted average of forecast of best ROC models from 1 to 4 quarters (Index3, Index4).

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Figure B-3
Recession probabilities with maximum, average and minimum indexes of all ROC models selected (Index1, Index2, Index3, Index4).

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Figure B-4
Recession probabilities with average of all ROC models selected (Index1, Index2, Index3, Index4) and leading financial indicator.

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Figure B-5
Market forecasts of recessions and models selected with out-of-sample ROCs.

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Table A-1
Real sector variables.

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Table A-2
Financial sector variables.

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Table A-3
Models of one year ahead forecasts.

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Table A-4
ROCs of one year ahead models.

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Table A-5
Models two years ahead forecast.

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Table A-6
ROCs of one year ahead models.

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Table A-7
One year ahead.

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Table A-8
Two years ahead.

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Table A-9
One year ahead.

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Table A-10
Two year ahead.

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(1)

Name Used in Regression	Definition	Name Used in Regression	Definition
Worldexp	World Exports	pib	GDP constant prices
sa_pib	GDP constant prices seasonal adjustment	abatave	Abatment of Chicken
abatcarne	Abatment of Meat	adubo	Fertilizer
balcom	Trade Balance	cambio	Nominal Foreign Exchange Rate
cimento	Cement	credpriv	Total Private Credit
credhab	Total Credit Housing	credpf	Total Credit Households
credtotal	Total Credit	defensivo	Agricultural Defensive
desempr	Unenployment Rate	desemprab	Open Unemployment Rate
desemproc	Non observable Unemployment rate	desocupserv	Non occupation rate
embmetal	Metal Packages	embpapel	Paper Packages
embplast	Plastic Packages	empformconst	Formal Employment Construction
empformpub	Formal Employment Government Sector	empformserv	Formal Employment Services
empformtot	Total Formal Employment	energia	Energy
energiacarga	Energy Load	energiadem	Demand Energy Load
expbasicos	Exports Basic Products	expmanuf	Exports Manufactured Products
export	Exports	ﬂuxoveic	Flux of Heavy Vehichles
folha	Payroll of Employees	horastrab	Hours Worked
ia_usa	Leading Index of Activities USA	ibc_br	Coincident Index of Activities Brazil
ibc_br_sa	Coincident Index of Activities Brazil seasonally adjusted	icc	Price Index
icc_exp	Consumer Confidence Index- Expctations	icc_fecom	Consumer Confidence Index FECOM
icc_pres	Consumer Confidence Index Present Situation	icea_fecom	Index of Economic Conditions FECOM
icms	State Tax	icms_sp	State Tax São Paulo
iec_fecom	Consumer Expectations Index	igpm	Price Index
impbk	Imports of Capital Goods	impinterm	Imports of Intermediary Goods
import	Total Imports	inadspc	Consultation to SPC
inaduse	Consultation to Users of Checks	inpc	Price Index
ipa_di	Price Index	ipa_og	Price Index
ipca12m	Price Index	mampli	Nominal Ample Payroll
mamplireal	Real Ample Payroll	nuci	Capacity Utilization
papel	Paper	pessoalocupind	Ocupied Individuals
pimcons	Industrial Production Consumption Goods	pimconsdur	Industrial Production Durable Goods
pimconssemidur	Industrial Production Semi Durables	piminterm	Industrial Production Intermediary Goods
pimtot	Total Industrial Production	prodauto	Total Production Automobiles
prodferro	Production Ore	prodmaqagric	Procuction Machines for Agriculture
prodmoto	Production of Motorcycles	prodoleolgn	Production of OIL and Gas
recfed	Tax Revenues	rendmedio	Avarege Salary Employed Individuals
pessoalocupind	Ocuppied Individuals seasonaly adjusted	pimcap	Industrial Production capital Goods seasonaly
pimcons	Industrial Production	pimconsdur	Industrial Productiom Durable Goods
pimconssemidur	Industrial Production Semidurables	piminterm	Industrial Production Intermediary Goods
pimtot	Total Industrial Production	sond	Industrial Survey
sond_exp	Expectations Industrial Survey	sond_pres	Present Situation Industrial Survey
vendascom	Total Sales Retail

Name Used in Regression	Definition
ibovespa	Bovespa Index
deb_spread	Spread of Debentures AA AAA-
ibrx100fim	Stock Market Index
M1	Monetary Aggregate
M2	Monetary Aggregate
M3	Monetary Aggregate
M4	Monetary Aggregate
selic_annual	Monthly Accumulated Selic Rate
selic_annual	Annual Accumulated Selic Rate
spread_pre	Average Spread of Bank Loans
spread_pre	Spread between Long Term and Short Term Public Bonds
swap120_fim	Swap DI 120 days end of period % p.a.
swap120_media	Swap DI 120 days end of period % p.a.
swap180_fim	Swap DI 180 days end of period % p.a.
swap180_media	Swap DI 120 days avarage % p.a.
swap30_fim	Swap DI 30 days end of period % p.a.
swap30_media	Swap DI 30 days % p.a.
swap360_fim	Swap DI 360 days end of period % p.a.
swap360_media	Swap DI 360 days average % p.a.
swap60_media	Swap DI 60 days average % p.a.
swap60_fim	Swap DI 60 end of period % p.a.
swap90_media	Swap DI 90 days average % p.a.
termo	Term Structure of Interest Rate
termo_real	Term Structure of Real Interest Rate

	Pr(recessao(t + K)) = f (X)
Number of regressors	K = 1	K = 2	K = 3	K = 4
m1	energia	sa_sond	ibrx100fim	ibovespa
m2	energia, impbk	sa_sond, M2	ibrx100fim,	ibovespa, impbk
			dloginaduse1
m3	energia, impbk,	as_sond, M2,	ibrx100fim,	ibovespa, impbk,
	icc_fecom	ibovespa	dloginaduse1,	sond_pres
			icc_fecom
m4	energia, impbk,	as_sond, M2,	ibrx100fim,	ibovespa, impbk,
m4	icc_fecom,	ibovespa,	dloginaduse1,	sond_pres, dlo-
	selic_anual	dlogicms	icc_fecom,	gempformpub
			ibrx100fim

Pr(recessao(t + K)) = f(X)
Number of regressors	K = 1	K = 2	K = 3	K = 4
m1	0.8710	0.5701	0.6637	0.6885
m2	0.5413	0.7070	0.7402	0.4497
m3	0.8878	0.8823	0.9443	0.9912
m4	0.7600	0.9492	0.9777	0.9990

	Pr(recessao(t + K)) = f(X)
Number of regressors	K = 5	K = 6	K = 7	K = 8
m1	ibovespa	icc_fecom	M2	icc_fecom
m2	ibovespa,	icc_fecom,	M2,	icc_fecom,
	sond_pres	balcom	dlogibovespa	impbk
m3	ibovespa,	icc_fecom,	M2,	icc_fecom,
	sond_pres,	balcom,	dlogbovespa,	impbk, energia
	empformtot	empformpub	desemp
m4	ibovespa,	icc_fecom,	M2,	icc_fecom,
	sond_pres,	balcom,	dlogbovespa,	impbk, energia,
	empformtot,	empformpub,	desemp,	expmanuf
	dlogprodauto	dlogimpbk	ibovespa

	Pr(recessao(t + K)) = f(X)
Number of regressors	K = 5	K = 6	K = 7	K = 8
m1	0.5098	0.6476	0.5421	0.9571
m2	0.6672	0.4771	0.4682	0.4095
m3	0.9147	0.9800	0.8569	0.9405
m4	0.9732	0.8777	0.6453	0.9383

	Pr(recessao(t + K)) = f(X)
	K = 1			K = 2		K = 3			K = 4
Number of regressors	ROC	Pseudo R2	MSE	ROC	Pseudo R2	ROC	Pseudo R2	MSE	ROC	PSEUDOR2	MSE
m1	0.7371	0.0980	0.2968	0.6650	0.0881	0.6600	0.0025	0.2977	0.6755	0.0025	0.2465
m2	0.6755	0.1304	0.2506	0.6803	0.1024	0.6606	0.0305	0.2722	0.6803	0.0305	0.2696
m3	0.9937	0.2869	0.2977	0.7239	0.1683	0.7416	0.0973	0.2889	0.7196	0.1780	0.2888
m4	0.9937	0.2893	0.2709	0.7196	0.1718	0.7075	0.1784	0.2897	0.7416	0.1784	0.2830

	Pr(recessao(t + K)) = f(X)
	K = 5			K = 6			K = 7			K = 8
Number of regressors	ROC	Pseudo R2	MSE	ROC	Pseudo R2	MSE	ROC	MAE	Pseudo R2	ROC	MAE	Pseudo R2
m1	0.7239	0.0027	0.2709	0.6869	0.0003	0.2852	0.6403	0.0824	0.2713	0.0134	0.0463	0.2852
m2	0.6277	0.0048	0.2963	0.6050	0.0228	0.2896	0.6044	0.0830	0.0727	0.6701	0.0651	0.2859
m3	0.8461	0.0973	0.2713	0.7620	0.0950	0.2624	0.8800	0.0797	0.1399	0.6866	0.0797	0.2875
m4	0.7166	0.0975	0.2873	0.7115	0.1055	0.2859	0.6819	0.1104	0.0851	0.8413	0.1104	0.2873

	Pr(recessao(t + K)) = f(X)
Number of regressors	K = 1	K = 2	K = 3	K = 4
m1	-5.32	-2.2034	-2.0167	-1.4100
m2	-2.2000	-2.2035	-2.0167	-1.4174
m3	-2.2000	-2.2035	-1.40065	-1.4176
m4	-2.2030	-2.2035	-1.4100	-3.9139

	Pr(recessao(t + K)) = f(X)
Number of regressors	K = 5	K = 6	K = 7	K = 8
m1	-3.5479	-2.8648	-2.4467	-1.9676
m2	-3.2471	-2.8648	-2.8648	-1.9698
m3	-3.2472	-2.8648	-2.8641	-1.9698
m4	-3.2500	-2.4467	-2.8647	-1.9698