Conference background

Background

Although many types of financial intermediaries and monetary substitutes have evolved over the past 30 years, most economists have placed little faith in broad monetary aggregates, since summation aggregation has long seemed inappropriate at high levels of aggregation over imperfect substitutes.

Milton Friedman (2010) famously stated that some good economists have been experimenting with the theoretically attractive idea of defining money not as the simple sum of various categories of claims but as a weighted aggregate of such claims, the weights being determined by one or another concept of the moneyness of the various claims. Specifically, William Barnett (1980) proposed selecting goods over which to aggregate in a manner consistent with the existing theory of aggregation over goods and using the Divisia index for monetary quantity aggregation (Swofford and Whitney, 1986, 1991). He is the inventor of the Economic or Divisia monetary aggregates, the minflex Laurent demand systems, and the asymptotically ideal model (AIM) demand system. Barnett was the first to produce reliable evidence regarding the existence of chaotic processes in economic time series and to propose a number of tests for nonlinearity and chaos motivated by the dynamics of nonlinear dynamical systems. Drawing on his findings that bifurcation boundaries for dynamical models often cross the parameter estimates’ confidence regions, his recent research has drawn attention to the loss of dynamical inference robustness produced by the common convention of simulating macroeconometric policy models only at the parameters’ point estimates (Heckman and Serletis, 2014).

Concretely, Divisia aggregation relies on consumer demand theory and the theory of economic aggregation.  This theory treats monetary assets as consumer durables such as cars, televisions, and houses (Hjertstrand, Swofford, and Whitney, 2016) with their services valued at the  margin by their rental or user cost prices. Assets are held for the flow of utility-generating monetary services they provide (Thornton and Yue, 1992).

The Divisia index tracks the quantity aggregator function, which depends only on quantities (Barnett, 2012). By equally weighting components, aggregation by summation can badly distort an aggregate. The simple sum monetary aggregates have produced repeated inference errors, policy errors, and needless paradoxes. In reality, financial assets provide different services, and each such asset yields its own particular rate of return. As a result, the user costs, which measure foregone interest and thereby opportunity cost, are not constant and are not equal across financial assets. The relative prices of U.S. monetary assets fluctuate considerably, and the interest rates paid on many monetary assets are not equal to the zero interest rate paid on currency. The aggregation-theoretic monetary aggregator function, which correctly internalises both macroeconomic and microeconomic effects, can be tracked accurately by the Divisia quantity index, constructed by using expenditure shares as the component growth-rate weights (Barnett and Chauvet, 2011). Therefore, aggregation theory favours the Divisia quantity index over the sum index as a measure of the quantity of an aggregated economic good, when the components are not perfect substitutes (Barnett, Offenbacher and Spindt, 1984). In contrast to the current prevalent simple sum monetary aggregates, the Divisia index takes into consideration the different liquidity levels and the expenditure weight of different monetary component growth rates within the monetary assets portfolio. Many researchers have demonstrated the superiority of Divisia monetary aggregates’ over the simple-sum money (e.g., Schunk, 2001).

During the last decades, Barnett’s academic publications has influenced profoundly the research conducted by a number of economists. Yet, despite the widespread appreciation of the advantages of Divisia monetary aggregation, Barnett’s work has had a surprisingly small impact on central bank monetary policies, at least as revealed to the public, or on availability of those aggregates from central banks to the public.

As a result, empirical work in monetary economics, throughout the past three decades and down to the present day, has continued, overwhelmingly, to rely on the readily available but conceptually flawed central bank simple-sum measures.  An exception is the Bank of England, which makes a Divisia monetary aggregate officially available to the public and is hosting a conference on the subject on May 23-24, 2017.  Many other central banks, which do have Divisia monetary aggregates available for internal use, do not make them available to the public.  For example, the European Central Bank has Divisia monetary aggregates, supplied to its Governing Council at its meetings, but not made available to the public. Similarly the Bank of Japan, which has published strongly favourable research with its Divisia monetary aggregates, has never made the data available to the public. The Federal Reserve and much of the scientific community continue to operate without theoretically-coherent and empirically-reliable indexes of monetary services (Belongia and Ireland, 2014).  This is despite the fact that the International Monetary Fund (2008) has made clear the superiority of the Divisia monetary aggregates. So far, there are many of cases in which Divisia money matters, but simple-sum money does not (Chrystal and MacDonald, 1994).  The Divisia monetary measurement approach has been produced in many countries, such as the USA, Britain, Japan, the Netherlands, Canada, Germany, Poland, Australia, China, Israel, and Switzerland, among many others (Barnett and Chauvet, 2011). The Center for Financial Stability in New York City maintains online an international library of research on Divisia monetary aggregation, including results for over 40 countries throughout the world.

At last, we can conclude that Global financial crisis has highlighted the importance of monetary policy, which is able to withstand adverse financial events. After the crisis, global policymakers have become aware about the weaknesses of conventional monetary policies and regulation. During financial crises, in particular when the policy rate was close to the zero lower bound, monetary authorities implement some unconventional instruments in order to provide a more expansionary policy. Many people still believe that monetary policy is not zero-sum game and the unconventional changes increase the overall economic benefits. Nowadays, we are looking for some one-best way. Also, the lack of adequate countercyclical prudential regulation was at the heart of the crisis. The capital adequacy rules of Basel I and Basel II were not sufficient to capture risks stemming from bank exposures to transactions and instruments, such as securitisation or derivatives, nor did they take into account the systemic risk posed by the build-up of leverage in the financial system. The effect on banks, financial systems and economies at the epicentre of the crisis was immediate (BCBS, 2010). So, the new Basel III framework focuses on the regulation of banks in the aftermath of the crisis by establishing, inter alia, higher capital and liquidity requirements, in terms of both quantity and quality. These standards should bring a greater financial soundness within the system. All in all, we are still searching for some solution which will substantially address the current economic and social difficulties and challenges in the aftermath of the Global crisis.

Therefore, what is the main question of this event? Considering this background, the decisive questions to be addressed are:

• How Important Are Economic (Divisia) monetary aggregates for contemporary economic policy?

• Do Divisia monetary aggregates deserve more attention from both academic scholars and policy-makers?.

References

Barnett, W. A. (1980). ‘Economic Monetary Aggregates: An Application of Index Number and Aggregation Theory’. Journal of Econometrics, 14(1): 11-48.

Barnett, W. A. (2012). Getting It Wrong: How Faulty Monetary Statistics Undermine the Fed, the Financial System, and the Economy. Cambridge and London: MIT Press.

Barnett, W. A. and Chauvet, M. (2011). ‘International Financial Aggregation and Index Number Theory: A Chronological Half-Century Empirical Overview’. In W. A. Barnett and M. Chauvet (Eds.). Financial Aggregation and Index Number Theory (pp. 1-51). Singapore: World Scientific Publishing.

Barnett, W. A., Offenbacher, E. K. and Spindt, P. A. (1984). ‘The New Divisia Monetary Aggregates’. Journal of Political Economy, 96(6): 1049-1085.

Basel Committee on Banking Supervision (BCBS) (2010; rev. June 2011). Basel III: A global regulatory framework for more resilient banks and banking systems. Basel: Bank for International Settlements.

Belongia, M. T. (2000). ‘Introductory Comments, Definitions, and Research on Indexes of Monetary Services’. In M. T. Belongia and J. M. Binner (Eds.). Divisia Monetary Aggregates: Theory and Practice (pp. 1-8). New York: Palgrave.

Belongia, M. T. and Ireland, P. N. (2014). ‘The Barnett Critique After Three Decades: A New Keynesian Analysis’. Journal of Econometrics, 183(1): 5-21.

Chrystal. A. K., and MacDonald, R. (1994). ‘Empirical evidence on the recent behavior and usefulness of simple-sum and weighted measures of the money stock’. Federal Reserve Bank of St. Louis Review, 76 (March/April): 73-109,

Friedman, M. (2010). ‘Quantity Theory of Money’. In S. N. Durlauf and L. E. Blume (Eds.). Monetary Economics (pp. 299-338). London: Palgrave Macmillan.

Heckman, J. J. and Serletis, A. (2014). ‘Introduction to Internally Consistent Modeling, Aggregation, Inference, and Policy’. Journal of Econometrics, 183(1): 1-4.

Heckman, J. J. and Serletis, A. (2015). ‘Introduction to Econometrics with Theory: A Special Issue Honoring William A. Barnett’. Econometric Reviews, 34(1-2): 1-5.

Hjerstrand, P., Swofford, J. L. and Whitney, G.A . (2016). ‘Mixed Integer Programming Revealed Preference Tests of Utility Maximization and Weak Separability of Consumption, Leisure, and Money,’ Journal of Money Credit and Banking, 48(7): 1547-1561.

International Monetary Fund (2008), Monetary and Financial Statistics: Compilation Guide, sections 6.60-6.63

Schunk, D. L. (2001). ‘The Relative Forecasting Performance of the Divisia and Simple Sum Monetary Aggregates’. Journal of Money, Credit, and Banking, 33(1): 272-283.

Swofford, J. L. and Whitney, G. A. (1986). ‘Nonparametric tests of utility maximization and weak separability for consumption, leisure and money.’  The Review of Economics and Statistics, 69(3): 458-464.

Swofford, J. L. and Whitney, G. A. (1991). ‘The composition and construction of monetary aggregates’  Economic Inquiry, 29(4): 752-761.

Thornton, D. L. and Yue, P. (1992). ‘An Extended Series of Divisia Monetary Aggregates’. Federal Reserve Bank of St. Louis Review, 74(November/December): 35-52.