Accounting for inequality

Train Night Market Ratchada in Bangkok, Thailand. nattanai chimjanon / Alamy Stock Photo

Essay

Accounting for inequality

By Robert M. Townsend

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Sitting in a Thai village with my collaborator, Anna Paulson, we began to wonder how to capture all the nuances of the reality of life of households and small entrepreneurs. We see a Thai family running a restaurant on the street side of their house, selling to customers, using eggs from the chickens running around the yard in front of the coop as well as items purchased from wholesalers. On the other side of the house are the family鈥檚 small herd of water buffalo, used for ploughing paddies in preparation for rice planting. Some of the eggs and rice are consumed by the household itself, but excess rice is sold in the market.  

With a keen eye, an observer might begin to see certain categories: the household capital (the house, coop, animals, and land) as assets; the restaurant sales as part of the profits from running a business (e.g., revenue less expenses) along with profits from the farm; and household consumption. Within each we can see both market and non-market (within household) transactions. While on a return flight to the US, another of my collaborators, Krislert Samphantharak, and I pondered the question of what do we really mean by income in such settings, anyway. We wondered if corporate financial accounting held some answers, though granted in a very different application of accounting relative to the norm. At the time we did not see where this was heading. 

Zoom out to the present day, literally at the time of writing, and take in a much broader macro view, seemingly unrelated at first. We can see that the perceived impact of globalization on inequality continues to drive both political outcomes and economic policy. In India, discontent in rural areas over jobs is reported to have costed Modi a decisive election win. In EU parliamentary elections, economic discontent is reported to have shaped the vote toward nationalist parties. Underlying these shifts is a narrative of geographic development traps, with regions experiencing relative declines in economic growth, employment, and productivity. In the US, the adverse impact of trade and manufacturing shocks that hit particular regions and sectors harder than others has given rise to more populist and authoritarian-leaning politics. So much so that both major parties are endorsing trade and immigration restrictions. African countries too are facing insurgency movements and renewed coups, reported to be driven in part by economic factors. 

Accurate measurement of households鈥 real economic wellbeing in these settings is key to formulating and implementing effective policies. Yet, ironically, political parties and the public sector proceed without the requisite detailed, targeted and consistent measurement. 

Domestic GDP growth is measured in national income accounts, yes, but the data we have does not allow us to look at the impact of that economic growth on various segments of the income distribution, despite anecdotal narratives to the contrary. That is, we do not have distributional accounts, as the data used to create the overall GDP are different from the data used in micro studies of inequality. 

Likewise, the data we do have, as in the US, do not allow us to know with much certainty the extent of concentration of wealth at the top of the distribution, despite frequently repeated statistics. That is, part of financial wealth is typically inferred from income flows alone. Income and wealth should be distinguished from each other and measured consistently. But attempts to do so at the macro level with current data reveal substantial errors and omissions. 

Further, the impact of the decline of income on households鈥 welfare in some regions could be better assessed with detailed balance sheet data. Drawing down previously accumulated assets, though not ideal, would paint a picture that is distinct from that of incurring ever increasing levels of debt. Though regional income is measured in the US, regional wealth is not. 

The sequel to the Thai village story, and the point of telling that story is this: We actually do know how to create the requisite data to answer all these questions accurately. This is what the monograph with Archawa Paweenawat is about. Start at the individual household level. First, apply the principles of financial accounting, building up income statements, balance sheets, and statements of cash flows from transactions data, the way it is done for corporate firms. But we apply that here to households and to small and medium enterprises (SMEs) which are the heart of many of the above-mentioned economies and crucial in advanced economies, for example as with supply chains. Looked at this way, real assets produce income as profits. Dividends from the enterprise, profits not reinvested nor saved, are part of consumption. Households that do not run SMEs are easier to conceptualize, with income from wages and salary, household assets for personal consumption and financial assets for saving, and most consumption acquired from the marketplace. 

In the case of both households and SMEs, savings (or deficits) in the income statement (adjusted for gifts and remittances) would be identical to the change in assets and liabilities in the balance sheet (adjusted for price appreciation and depreciation in value). This is what is meant by consistent financial accounts.

Within household and across household community transactions can also be measured, knowing the trading partners (and made easier in other settings with electronic records from banks and fintech apps). Then we can aggregate up these various household and SME financial accounts to create consistent village, community, regional, and national integrated accounts, following, for example, guidelines already offered by the US Department of Commerce. We can then see the balance of payments and financing across regions.

To get an idea of what this could look like, one can go to data that has already been created from a long-term survey project conducted in Thailand, put into a consistent integrated accounting framework. From these data and accounts, one can quantify the impact of regional integration in trade and capital flows, as historically Thailand has been a liberal emerging market economy, but one with winners and losers. The impact in the data paints a different picture across the diverse regions of the Thai survey. We have found that it is not true that one story fits all. 

Likewise, thinking about the impact of repression, one can assess, with the data intimately linked to the modeling, the diverse heterogenous impact of trade and financial restrictions, as proposed by policymakers, at the level of individual households, distinguished by wealth and productivity, different in different regions. One can also assess impact at the level of the regional aggregates.  Anecdotal profiles of impact are replaced by solid targeted measurement.

As detailed in Inequality and Globalization, these steps can then be implemented in the US and other countries. We outline how to 鈥渟tart from scratch鈥 at the micro level, from data and surveys, but utilizing and strengthening existing data on income and wealth, from the Bureau of Economic Analysis and the Federal Reserve respectively. We are on our own at the moment, with small teams working on this in the US and Thailand, but this effort could be scaled if only there were the requisite social and political will. 


Robert M. Townsend is the Elizabeth and James Killian Professor of Economics at the Massachusetts Institute of Technology. He is the author of Distributed Ledgers: Design and Regulation of Financial Infrastructure and Payment Systems, Chronicles from the Field: The Townsend Thai Project, Households as Corporate Firms: An Analysis of Household Finance Using Integrated Household Surveys and Corporate Financial Accounting.