Cointegration, Dependency and Manufacturing (24-IV-09)

Chile - USA (1981-2008)

Peru - USA (1981 - 2008)

These graphs show –for a naked eye- a similar cycle over time, besides differences on timing and amplitude, there is a similar number of boom and boost processes. A first question to analyze is the existence of cointegration between those series, and if the answer is affirmative to evaluate the dependency of some from one.

 

Cointegration concept comes from econometrics and it is related to time series which evolve over time in a similar pattern, cointegration does not imply causality between the variables analyzed, it implies a similar concept of parallel lines in geometry.

 

On the other side dependency theory in economics, implies the existence of a center and a periphery, equivalent to solar system in astronomy, the planets does not have exact orbits, but they are not comets drifting on the outer space. The dependency concept tells of an economy that is the center for periphery economies, which essentially are tied up to the evolution of the center.

 

This note founds that Chile and Peru manufacturing sector are periphery economic activities to the USA industrial sector on the long run, obviously in the short run a periphery sector may drift away, but sooner or later return to its orbit. A simulation is run from August 2006 up to December 2008, when Peru has a new presidential tenure in July 28^th 2006, which shows a Peru industrial sector drifting-up, and then a forecast is made to evaluate how much economic contraction will face Peru to be back on track.

 

The monthly series are taken from International Monetary Fund’s International Financial Statistics Compact Disk disseminated March 2009. Only series from Chile and Peru are chosen from South America due lack of availability for other countries, only USA series will be taken from 24 advanced economies (IMF lingo), as center country. The series start in January 1979 because Peru is the constraint, until December 2008 because is most recent available data from USA. The codes are […66EY.ZF…] for Chile and Peru, and […66…ZF…] for USA; which is available here.

 

A first step is taking logarithm of each series, then to evaluate the existence of unit root for each one, which is accepted. A cointegration test between Chile, Peru and USA is rejected with zero lags, but a loop from 1 to 60 lags is run to find 12 lags (a calendar year) as appropriate to accept cointegration between the analyzed variables. The evaluation is constraint until July 2006, since Peru has a new presidential tenure since August 2006.

 

Two approaches were tried to model the dependency of Peru and Chile to USA. The unsuccessful one was an Error Correction Model (ECM) which shows a strong equilibrium relationship between Peru and Chile, but the equilibrium error component was nil for Chile equation and strong for Peru; but in any circumstance was possible to reject a null hypothesis for USA inclusion in the equilibrium relationship or in the equilibrium error.

 

The second and successful approach was a Vector Autoregressive (VAR) model with USA as exogenous component. The lag period was 12, since this length was found as adequate on the cointegration analysis described above. The computer code in RATS is here, and the output results are here.

 

The first null hypothesis tested for no relation between Chile and Peru is rejected for each equation and therefore the naked eye observation was correct. A second set of null hypothesis for each USA coefficient being zero in both equations is carried out, to find them rejected and to conclude that USA industrial sector has influence on Chile and Peru manufacturing sector, in the impact multipliers. A third set of null hypothesis for equilibrium multipliers of USA being zero is carried out, to find them accepted; this unexpected outcome is interpreted as neutrality on the long run of the level of USA industrial activity for Chile and Peru manufacturing sectors, only if USA variable become constant which never have been observed. A fourth set of null hypothesis for equilibrium unitary elasticity between Chile and Peru is carried out, to find them rejected; this outcome allows concluding that USA individual shocks in Chile and Peru become permanent for the level of manufacturing activity.

 

Those four sets of null hypothesis are re-run with a Seemly Unrelated Regression (SUR) model with similar specification in order to evaluate cross equation restrictions. The previous four null hypotheses are evaluated and similar conclusions are obtained. The fifth null hypothesis of USA impact coefficients with similar values vis-à-vis for Chile and Peru is carried out, to find them rejected; this outcome allows concluding differentiated short run impact between Chile and Peru, nevertheless for both countries the equilibrium multiplier for USA is zero. Finally, a sixth null hypothesis for null intercept in Chile and Peru is carried out and accepted; this outcome allows to conclude that long run average level of manufacturing in Chile and Peru is the long run multiplier of Peru and Chile –respectively- multiply by the average level of industrial activity in USA.

 

The third and sixth null hypotheses are imposed in a new estimation on the SUR model in order to produce a forecast outside the boundaries of the estimation, which are January 1979 and July 2006. The forecast values are plotted in graphs for Chile and Peru showing an interesting feature which differentiates Chile and Peru; while Chile forecast values are close to observed values, Peru forecast values are systematically below observed values.

 

A first econometric conclusion is the existence of cointegration between Chile, Peru, and USA. A second econometric conclusion is the dependency of Chile and Peru with USA which is coherent with the economic dependency theory. A third conclusion is Chile manufacturing sector is on track, and its contraction will mirror USA industrial contraction. A fourth conclusion is Peru manufacturing sector is off track, and its contraction will be more than proportional to USA industrial contraction.

 

 

Chile Forecast (August 2006 - December 2008)

Peru Forecast (August 2006 - December 2008)

Chile and Peru gap between observed and forecast values

Advertisement

We are in the same boat (17-III-09)

In July 2007, I did a series of graphs with quarterly data that I copy below with IFS compact disk from International Monetary Fund, in order to find how syncronizated was Peru and the countries around it with the industrialized countries.

The spreadsheet is here, the tab called “Data” contains all numbers for the graph, and the numbers above the red line are taken from IMF compact disk with no modification, column F contains IMF codes for each variable.

Besides obvious lags, the syncronization is evident and only differences are due to national policies of how to face boom and bust cycles. The most pathetic example is Peru with Garcia’s first term where the policy was against the tide, and economic failure established a regional record.

Colombia - Peru (Manufacturing Production)

In this graph is possible to see how maximum and minimum values through the cycle are in sync between Colombia and Peru for manufacturing production.

Chile - Peru (Manufacturing Production)

In this graph is possible to see how maximum and minimum values through the cycle are in sync between Chile and Peru for manufacturing production.

Just a Coincidence?

Next three graphs show the relation of Colombia, Chile, and Peru manufacturing production index with the IMF’s Advanced Economies industrial production index.

Advanced Economies - Colombia (Manufacturing Production)

Advanced Economies - Chile (Manufacturing Production)

Advanced Economies - Peru (Manufacturing Production)

In the graphs for Colombia and Chile, for early 90s there is breakdown in the relation between both countries and the Advanced Economies, an explanation for this could be find in graph below that shows a similar gap between USA and the Advanced Economies. Therefore Colombia and Chile are more in sync with USA than with the Advanced Economies.

Advanced Economies - USA (Manufacturing Production)

Finally, in Peru graph is possible to see how Garcia in his first term (1985-1990) had two all time records, one for maximum manufacturing production with a peak of 8% in the beginning of his tenure and other for minimum manufacturing production with a trough of -10% at the end of his tenure.

And now again, Garcia likes to sail against the tide and for sure as before Peru will sink at unthinkable degree, due to Garcia manic need to negate external reality.

Sun Nov 24, 2002 4:20 pm

Paleografía & Econometría

 

Hola Javier:

Algunos detalles previos antes de responder tu último mensaje de
manera detallada. Cuando estudiaba Historia, el curso de Paleografía
era clave porque si no se sabía leer los documentos del siglo XVI no
podías hacer inferencia científica. La idea de distribuir las bases
de datos responde a la actitud usual de un archivero de colocar
públicamente las información disponible.

Respecto a lo que se puede hacer con la base de datos, hasta
donde aprendí Econometría lo mas práctico es hacer ARIMA-X. Yo no
haría nada con ciclo porque em algún monento creí hallar para el
Perú un ciclo de 11/13 años con 8/9 de subida y 3/4 de bajada.
Espero hallar mas series para poder hacer estudios de ciclo.

Aquí va sobre tu último mensaje:

1) No recuerdo bien si el método de “leading” también implicaba
hallar “coincident” y “lagged”. O si las técnicas nuevas permiten
hacer sólo “leading” y olvidarse de los otros dos.

2) Otro tema, es que si entendí bien del método que aplicaste es
que impone simetría en el ciclo, la pendiente de subida es igual a
la de bajada. ¿O me equivoco?

3) Los datos son tal cual los he encontrado en el Instituto, y
hasta donde entiendo son tal cual son enviados por las OSE (Oficinas
Sectoriales de Estadística). El problema es que no sabemos el umbral
entre definitivos y preliminares en cada serie.

4) Lo impresionante no lo se. Espero poder mostrar series
mensuales de indicadores de volumen de los cinco países limítrofes
del Perú, y de allí quizas se pueda desprender en un corte
transversal el desempeño del Peru.

5) El PBI por el lado del gasto tiene en todas partes el grave
problema de medir el consumo privado. Sin encuestas a hogares es
difícil poder tener otra alternativa que obtenerlo residualmente, lo
cual es grave para un componente que suele ser 70%/80% del gasto
total.

6) Al presente, el INEI solo mide el consumo privado anualmente,
usando como herramienta central las ENAHO. Que han tenido una vida
accidentada y se han concentrado básicamente en el cuarto trimestre
del año.

Un abrazo, Farid

— In MacroPeru@y…, “JAVIER” <jkapsoli@m…> wrote:
> Hola Farid
>
> Perdona que recien te conteste, el viernes estuve “off duty”.
>
> Efectivamente tambien se pueden construir indices rezagados y
> coincidentes. Para nosotros, nuestro interes es basicamente saber
> hacia donde va el nivel de actividad con algo de antelacion.
>
> Si hacemos predicciones de algunas de las variables que componen
el
> indice (las que tienen menor nivel de adelanto) podemos tener una
> aceptable idea de la evolucion proxima de la economia. Este
ejercicio
> esta en el paper. Para el ano teniamos un 4.7.
>
> A estas alturas conocido ya el dato oficial del 3er trimestre, a
pesar
> de que creo que el 4to trimestre va a estar un poco menos dinamico
> parece dificil que el ano cierre muy alejado del 4.7, 4.5 deberia
ser
> el dato final, en mi opinion. Impresionante no??
>
> A proposito, vamos a tener que hacer un update de nuestro indice
dado
> que los files que has puesto en la red muestran que todos los
datos
> mensuales de este ano han cambiado. En particular el 2do trimestre
ha
> pasado de 5,3 a 6,1. Fuerte, no?? hay alguna explicacion de
esto??
> han hecho una revision metodologica??
>
> Creo que debo felicitarte por este extraordinario acto de
> transparencia (el primero que yo recuerde) de mostrar de una
manera
> pristina la forma como se construyen las estadisticas en nuestro
pais!!
> Imagino que todos miembros de esta lista estaran igual de
contentos
> que yo. Ahora hay harto ingrediente para preparar los guisos que
> tanto nos gustan!
>
> Una ultima cosa Farid, antes que me olvide. El INEI publica algun
> documento donde se muestre el PBI por el lado del gasto?? No lo
hacen,
> me parece, o me equivoco?? No deberian hacerlo?? Ahora estamos
> basicamente dependientes de las estimaciones del Central. Por que
el
> INEI no presenta tambien sus estimaciones, si es la institucion
> rectora del sistema estadistico??
>
> Ah! sobre el Indice de MAcro, la verdad sobre el IMAC es muy poco
lo
> que se, lo unico que se a ciencia cierta es que no es un leading.
De
> lo que he conversado con Elmer, puedo inferir que es algun tipo de
> modelo dinamico, un ECM creo. Tal vez Elmer o alguien de Macro
pueda
> darnos algun otro detalle.
>
> Un abrazo a Todos
>
> Javier
>
> > Hola Javier:
> >
> > Estuve leyendo ayer tu trabajo sobre “leading” y no me quedo
> > claro si tambien habrán “Coincident” y “Lagging”. Aquí te
transcribo
> > un artículo que encontre a través de Yahoo! donde curiosamente
lo
> > hace una .ORG, no un .GOV o un .COM. ¿Como se clasificaría el
> > indicador de MacroConsult?
> >
> > Gracias, Farid.
> >
> > ********************************************
> >
> > U.S. Leading Economic Indicators Hold Steady
> >
> > Nov. 21, 2002
> >
> > More data and charts at http://www.globalindicators.org
> >
> > The Conference Board announced today that the U.S. leading,
> > coincident and lagging indexes all held steady in October.
> >
> > Strong real money growth and lower unemployment claims in
October
> > offset weak consumer expectations and faster deliveries, as
measured
> > by vendor performance.
> > The coincident index performance continues to suggest a
recovering
> > yet fragile economy. Industrial production has shed some of its
> > gains from the first half of the year and nonagricultural
employment
> > has essentially remained unchanged. Moderate growth in personal
> > income and manufacturing and trade sales continue to sustain
> > economic growth.
> > Although the leading index has been flat or declining over the
past
> > five months, it is only 0.2 percent below its level from April
of
> > this year.
> > Leading Indicators. Six of the ten indicators that make up the
> > leading index increased in October. The positive contributors to
the
> > index – beginning with the largest positive contributor – were
real
> > money supply*, average weekly initial claims for unemployment
> > insurance (inverted), manufacturers’ new orders for nondefense
> > capital goods*, building permits, interest rate spread, and
> > manufacturers’ new orders for consumer goods and materials*. The
> > four negative contributors – from the largest negative
contributor
> > to the smallest – were index of consumer expectations, vendor
> > performance, average weekly manufacturing hours, and stock
prices.
> >
> > The leading index now stands at 111.4 (1996=100). Based on
revised
> > data, this index decreased 0.4 percent in September and
decreased
> > 0.2 percent in August. During the six-month span through
October,
> > the leading index decreased 0.2 percent, with six of the ten
> > components advancing (diffusion index, six-month span equals 40
> > percent).
> >
> > Coincident Indicators. Two of the four indicators that make up
the
> > coincident index increased in October. The larger contributor to
the
> > index was personal income less transfer payments*, followed by
> > manufacturing and trade sales*. Industrial production decreased
in
> > October while employees on nonagricultural payrolls held steady.
> >
> > Holding steady, the coincident index now stands at 115.1
(1996=100).
> > Based on revised data, this index held steady in September and
> > increased 0.1 percent in August. During the six-month period
through
> > October, the coincident index increased 0.6 percent.
> >
> > Lagging Indicators. The lagging index held steady at 100.0
> > (1996=100) in October. Two of the seven components declined in
> > October. The negative contributors to the index – beginning with
the
> > larger negative contributor – were commercial and industrial
loans
> > outstanding* and change in CPI for services. The positive
> > contributors to the index were average duration of unemployment,
> > change in labor cost per unit of output*, ratio of consumer
> > installment credit to personal income*, and ratio of
manufacturing
> > and trade inventories to sales*. Average prime rate charged by
banks
> > held steady in October. Based on revised data, the lagging index
> > decreased 0.5 percent in September and decreased 0.2 percent in
> > August.
> >
> > Data Availability. The data series used by The Conference Board
to
> > compute the three composite indexes and reported in the tables
in
> > this release are those available “as of” 12 Noon on November 20,
> > 2002. Some series are estimated as noted below.
> >
> > *Notes: Series in the leading index that are based on The
Conference
> > Board estimates are manufacturers’ new orders for consumer goods
and
> > materials, manufacturers’ new orders for nondefense capital
goods,
> > and the personal consumption expenditure deflator for money
supply.
> > Series in the coincident index that are based on The Conference
> > Board estimates are personal income less transfer payments and
> > manufacturing and trade sales. Series in the lagging index that
are
> > based on The Conference Board estimates are inventories to sales
> > ratio, consumer installment credit to income ratio, change in
labor
> > cost per unit of output, and the personal consumption
expenditure
> > deflator for commercial and industrial loans outstanding.
> >
> > The next release is scheduled for December 19, 2002 at 10 A.M.
ET.
> >
> > For further information contact:
> > Frank Tortorici
> > (1) 212 339 0231
> > f.tortorici@c…
> >
> > Ken Goldstein
> > (1) 212 339 0331
> > ken.goldstein@c…
> >
> >
> >
> >
> > To unsubscribe from this group, send an email to:
> > MacroPeru-unsubscribe@e…
> >
> >
> >
> > Your use of Yahoo! Groups is subject to
> http://docs.yahoo.com/info/terms/
> >
> >
> >
>
> —
> NeoMail – Webmail that doesn’t suck… as much.
> http://neomail.sourceforge.net