The mainstream things taught in economics textbooks are increasingly being questioned. Infact not just being questioned but proven wrong when checked against real time evidence.
Stefan Avdjiev, Robert McCauley and Hyun Song Shin point to similar problems with International Finance.
Capital flows are traditionally viewed as the financial counterpart to savings and investment decisions. In textbooks, the unit of analysis is the national GDP area, and what is ‘external’ or ‘internal’ is defined with reference to its boundaries (e.g. Krugman et al. 2012, Obstfeld and Rogoff 1996). This perspective naturally leads to a focus on net capital flows between countries, and the current account indicates the borrowing requirement of the country as a whole.
Textbooks typically add two further features which appear innocuous but turn out to be hugely consequential for the conclusions. The first assumes that all sectors in the economy (firms, households, government) can be summed into one representative decision-maker. The second is that each economic area has its own currency and that currency is primarily used in that economic area. The upshot of these two additional assumptions is a ‘triple coincidence’ between: (1) the economic area defined by the GDP boundary; (2) the decision-making unit; and (3) the currency area.
No doubt, this is an elegant simplification for analytical purposes. However, as we argue in a paper presented at last October’s Economic Policy panel, and published recently, the assumption of the triple coincidence can mislead in a world of multinational firms and international currencies in which financial flows are important in their own right (Avdjiev et al. 2016).
They point to three evidences:
Consider three examples of how the triple coincidence can mislead.
The first example is cross-border banking and the subprime mortgage crisis in the US. Bernanke (2005) famously coined the term ‘global saving glut’ to explain how the large US current account deficit could coexist with easy US financial conditions during the run-up to the financial crisis. In line with the triple coincidence, Bernanke attributed these to excess saving in emerging economies combined with their preference for US financial assets.
In the event, however, emerging market investors were not the ones to bear the big losses from subprime mortgage securities. Instead, it was European investors, notably the banks, which took the hit. McGuire and Von Peter (2012) and Shin (2012) showed how European banks funded subprime portfolios by the ‘round-tripping’ of dollar funds from the US and back again. The dollars raised by borrowing from US money market funds flowed back to the United States through purchases of securities built on subprime mortgages (Figure 1). Since the outflows to Europe were matched by the inflows from Europe, the changes in net flows were negligible, so that these flows were virtually invisible to someone who looked only at the current account balance.
So gross flows are as important.
Other two examples look at why USD appreciated despite US running a Current account deficit and Korean won depreciated despite Current account surplus.
What is the way? Go bottom up or top down:
Post-crisis, there has been a growing recognition that it may no longer be enough to build the analytical framework of international finance purely around savings and investment decisions. In his Ely lecture at the 2012 American Economic Association meeting, Obstfeld (2012, p. 3) concludes that “large gross financial flows entail potential stability risks that may be only distantly related, if related at all, to the global configuration of saving-investment discrepancies” (see also Borio and Disyatat 2011, 2015).
Nevertheless, challenges lie ahead when we seek to move from a recognition of the inadequacy of our current accounting classifications towards a workable general equilibrium framework that transcends the triple coincidence. General equilibrium models deal with GDP components such as consumption and investment, and hence start with the GDP area as the unit of analysis. However, financial flows and balance sheets often do not map neatly on to the traditional macro variables that are measured within the GDP boundary.
To make progress, we can go in one of two directions. The first is to drill down to individual firms and households, using micro data. The second is to go in the opposite direction, and ‘drill up’ to use aggregate global data.
The rationale for the second strategy is that if we focus on global categories, such as global financial conditions or global appetite for risk, the lack of coincidence between the GDP areas and balance sheets matters less. At the global level, the numbers all add up to the same global total. Bruno and Shin (2015) is an example of how the global banking system can be analysed in just such a global model, and Cohen et al. (2016) explain how the BIS Global Liquidity Indicators can be motivated as indicators of global conditions.
Actually all this global talk only leads to more confusions. It should be taking each country differently and drill down the micro data.
I mean there is atleast some talk happening at conference/research level. But textbooks and teaching broadly remain unchanged.