5 Conclusions

1. This chapter developed the basic accounting tools of the national product accounts and the balance of payments.

2. It also introduced the concept of external wealth, and related it to the balance of payments.

3. These tools will be used throughout the rest of the book.

The science of macroeconomics would be impossible without data, and the vast majority of the data we employ emerge from the efforts of official statisticians around the world. Despite all the statistical discrepancies, and even the occasional errors of omission and commission (see Side Bar: Beware of Greeks Bearing Statistics), we would be lost without these measures of macroeconomic activity.

This chapter has illustrated some important accounting concepts and has highlighted some unusual and intriguing features of the current international economic system. We have seen how a consistent system of national income and product accounts allows countries to track international trade flows (including trade in intermediate goods), cross-border factor income flows, and unilateral transfers. We have also seen how these net resource flows of goods and services can be matched against a parallel set of net payment activities involving assets in the balance of payments accounts. Finally, we have seen how the flow of trades in assets can be combined with capital gains and losses to track the evolution of a nation’s stock of external wealth, an important part of its total wealth, as recorded in the statement of the net international investment position.

In the remainder of the book, we make extensive use of the concepts introduced in this chapter to develop theories that explore the global macroeconomic links between nations.

Cases where governments had deliberately falsified their macroeconomic data

Beware of Greeks Bearing Statistics

It is important, but rather sad, to note that when it comes to national statistics, we cannot believe everything we read. Over the years numerous governments have been suspected of fiddling with their official data for various purposes, as indicated by the following examples:

  • Greece. In 2001 Greece was allowed to join the Eurozone. One of the criteria it had to meet in order to join was that its budget deficit could not be more than 3% of its GDP. Greece met this requirement according to its official statistics. In November 2004, after it had been allowed to join the Eurozone, Greece admitted its 2003 budget deficit was really 3.4%, twice as large as it had previously claimed. In fact, the budget deficit had not been below 3% since 1999. The EU was not amused. Greece continued to publish incorrect or manipulated data (including a 25% upward adjustment to GDP to take into account “black economy” activity such as prostitution). By inflating its GDP, Greece made its budget deficit position look better than it was, which may have allowed Greece to borrow from other countries on favorable terms. When the euro crisis hit in 2008–09, the full horror of Greece’s weak economic and fiscal position became clear, by which point the fiasco forced other Eurozone nations and the IMF to provide emergency funding in 2010. Greece eventually defaulted in 2011, went into a deeper depression, and the economic and political ramifications (e.g., austerity policies, the collapse of the Cyprus banking system in 2013, and undermined confidence in other weak economies) have continued to threaten the survival of the euro project itself.
  • Italy. In 1987 Italy was considered much poorer than northern European countries. But its statisticians also decided to increase GDP by 15% after some guesswork to account for the black economy. Instantly, Italians had a higher official GDP per person than the British, an event known as il sorpasso. Not that this made any Italians actually feel richer.
  • Argentina. After its 2001 crisis, a new populist government took over but faced problems with high and persistent inflation. To “solve” this problem, the government “reorganized” its official statistical bureau, which then started publishing much lower, and highly suspicious, inflation data. Lower inflation also helped the government avoid larger costs of indexed benefits and allowed the government to claim it had solved the inflation problem. Few believed these published data were true.
  • China. In the 2005 International Comparison Program by the World Bank, the estimate of China’s yuan price level came in much higher than had been expected. This had various implications: dividing nominal yuan income by the price level made China look quite a bit poorer. And higher prices made China’s real exchange rate less undervalued, or even overvalued. Since poorer countries usually have lower price levels, both of these impacts had the effect of making China’s exchange rate look more fairly valued, given its standard of living. This came about at a time when China was under considerable political pressure to appreciate its currency. But skeptics doubted whether the data were totally plausible, because the change in the yuan price level since the previous ICP was much larger than that implied by China’s own official inflation data over the same period.