Economic Regression Analysis: Nigeria's Export and Service Sector

Introduction and Scope

This essay covers a number of economic and quantitative analysis topics — roughly six in total. Those topics, in order, are: a focus on a non-core variable and model for the country of Nigeria; an analysis of the World Bank World Development Indicators (WDI) model; comments on regression and the validity questions arising from within it; the general problems and pitfalls of regression analysis; whether any variables in the author's model have problems related to non-stationarity; and, finally, suggested changes to the models discussed based on the outcomes and policy implications that can be drawn from this analysis.

Nigeria's Non-Core Variable: The Service Sector

The government and economy of Nigeria heavily focuses on exports of its vast mineral, petroleum, and natural gas resources. An industry that has been something of a microcosm compared to those exports in recent years and decades is the service sector (Government of Nigeria, 2012). In many ways, Nigeria is the polar opposite of the modern-day United States, which has a higher — and growing — service economy, while its manufacturing, especially of simpler goods, is declining rapidly.

The government of Nigeria reports that the service sector is growing rapidly. However, it is also noted that economic shocks have an immediate impact on this burgeoning industry. For example, if a pipeline in Nigeria is bombed — which has happened before — the service sector feels the effects immediately. The variable that should be assessed for its impact on the service sector and on how well it grows is overall exports from Nigeria. There has been, and should continue to be, a causality-based relationship between the rise and fall of exports and the ensuing effects on the service sector.

Given the depth and breadth of economic knowledge available, one would expect at least some delay between the "cause" of exports being stunted and the "effect" of the service sector retracting or otherwise struggling to grow at the same level, if at all. The expected results of any model — regression analysis or otherwise — would be that the service sector rises and falls along with export performance, but that this is a reactionary relationship: the service sector responds to the variables and performance of exports in Nigeria.

To expand on the model referenced in the prior section, it is noteworthy that Sub-Saharan Africa had meager growth in 2008 but did not fall nearly as far in 2009 as other regions of the world, including Eastern Asia, Europe, and Central Asia. This, combined with the fact that rising incomes cause poverty to decrease (and vice versa), means that the impact on the service sector as well as on poverty in general would be much more muted than in other countries.

WDI Model Analysis

The aforementioned pattern — in which rising exports buffer and support the service sector in Nigeria, and the reverse holds as well — is supported by WDI data, even if the reactions would be much smaller than perhaps expected. This makes it harder to attribute small rises and falls directly to export levels. Nevertheless, some useful outcomes and analysis remain possible.

As will be elaborated upon in the next section, the core problem with regression analysis is differentiating between causality and correlation. The first question that should be asked is whether it makes logical sense for the service sector to be affected by exports. The answer is a resounding "yes," for two major reasons.

Regression Validity and Causality

First, many of the services performed by the service sector are rendered for businesses and individuals who earn wages through the export industry. If export levels are suffering, this will result in lower wages and reduced demand for services — both from the industries themselves and from their workers.

The second reason is that exports constitute the bulk of what Nigeria has to offer economically. If the core of its economy takes a blow, all ancillary industries will suffer at least as much. This is analogous to the international argument that when the United States gets sick, the world catches a cold. When an economic heavyweight — whether a nation or a sector — stumbles, the effects can be wide-reaching, both domestically and internationally. When Nigerian oil exports are impacted, for example, it almost always has an effect on fuel prices around the world.

As for the regression itself, it is clear that exports and service sector performance have a strong relationship, but it is not absolute. It is not a 1:1 relationship, and there are other actors that can mitigate or aggravate a situation. A useful example can be found in countries like Mexico, where the price of corn has had significant impact due to the high use of ethanol as fuel. Returning to Nigeria, viewing any relationship from a 1:1 perspective — where one variable directly and exclusively drives another — is almost always an oversimplification, and the validity of any results will be affected by the fact that other events and situations can and do influence both exports and the service sector simultaneously.

Additionally, the impacts between the two variables are mostly one-directional. If the service sector were to stumble, the likelihood that this would affect exports in any demonstrable way is very low, unless the service in question is something vital to the export industry. Government policy and external events can affect one or both groups simultaneously or independently. For example, price caps in the service sector would almost certainly harm that sector considerably, while the export industry would probably remain unaffected — unless the quality of available services deteriorated to such a degree that export capacity itself was impaired. That would constitute an exception in which the service sector's decline feeds back into export performance negatively.