The Unassuming Economist

In a recent column for VoxEU CEPR, Elwyn Davies, Mary Hallward-Driemeier and Gaurav Nayyar of the World Bank write about prospects of services-led development and the role of small firms in driving it.

“This column argues that the services sector deserves more credit for helping drive economic transformation than it generally receives. Using firm-level data from 20 developing economies, the authors find that while services establishments are smaller than manufacturing establishments, this matters less for their productivity. Services firms can scale up without sizing up through investments in human and other more intangible forms of capital can leverage the diffusion of digital technologies. “

This theme is elaborated upon further in their book, At Your Service?: The Promise of Services-Led Development (2021), which “assesses the scope of a services-driven development model and policy directions that maximize its potential”.

Related Reading:

Services Development and Comparative Advantage in Manufacturing

Global services value chains: A new path to development

By Philip Hans Franses and Max Welz

“This paper deals with forecasting low-frequency macroeconomic variables, when data
are available for a reasonably large number of countries or states. As many macroeconomic
variables have a stochastic trend, the forecasting methodology also addresses potentially
common stochastic trends. In this paper the particular focus is on forecasting annual real
GDP (Gross Domestic Product) growth rates in Africa.”

To read more click here.

Source: World Bank Global Economic Prospects (2022)

“The global recovery is set to decelerate markedly amid continued COVID-19 flare-ups, diminished policy support, and lingering supply bottlenecks. In contrast to that in advanced economies, output in emerging markets and developing economies (EMDEs) will remain substantially below the pre-pandemic trend over the forecast horizon. The global outlook is clouded by various downside risks, including renewed COVID-19 outbreaks due to Omicron or new virus variants, the possibility of de-anchored inflation expectations, and financial stress in a context of record-high debt levels. If some countries eventually require debt restructuring, this will be more difficult to achieve than in the past. Climate change may increase commodity price volatility, creating challenges for the almost two-thirds of EMDEs that rely heavily on commodity exports and highlighting the need for asset diversification. Social tensions may heighten as a result of the increase in between-country and within-country inequality caused by the pandemic. Given limited policy space in EMDEs to support activity if needed, these downside risks increase the possibility of a hard landing.

From Bloomberg:

“Housing markets are red hot, with prices up more than 18% from November 2020 to November 2021. That’s an acceleration over the previous two years, which saw increases of 4% and 8% each. It’s also a faster rate than the U.S. experienced during the housing boom of the 2000s that preceded the Great Recession.

That comparison is causing some heartburn. “Are we in another housing bubble?” asked Mark Zandi, chief economist at Moody’s. The consensus, shared by Zandi, is that the answer is no — or, at least, that today’s bubble is different and less dangerous than the last one. Lending standards are more strict than they were 15 years ago, for example, which ought to mean that fewer homeowners are at risk of defaulting if prices fall.

CNN, though, found a reason for pessimism in that optimism. “The good news is that few economists believe that the current run-up in housing prices is a bubble that’s about to burst, taking the economy down with it,” Chris Isidore of CNN Business wrote on Oct. 27, 2021 before adding ominously, “The bad news is that practically no one was worried about the housing bubble in 2007, either.”

But there’s another reason for sanguinity about the current housing boom: We may have misunderstood the last one all along.

The economists David Beckworth and Scott Sumner have argued that the timing of the last housing bust does not line up with the conventional wisdom that it played a central role in the recession that began in December 2007. The housing market peaked in early 2006, and sustained nearly two years of decline before the economy stopped growing as unemployment stayed low.

Kevin Erdmann — the author of a new book about housing, “Building from the Ground Up,” and a colleague of Beckworth and Sumner at George Mason University’s Mercatus Center — has more recently challenged the claim that the U.S. built too many houses back then. He points out that spending on housing didn’t grow any faster than spending on other consumption goods during the boom (or the preceding decades). The notion that the price increases of 2000-2007 were unsustainable, he points out, also doesn’t match the experience of other countries. The U.K. had a larger increase, a shorter and less severe decline, and a stronger rebound.

Erdmann does not deny that average home prices rose too much in some metropolitan areas during that period. But these spikes were a function of too little homebuilding, not too much. Prices rose fast in two types of cities: those with tight constraints on supply (including New York and San Francisco) and those that dealt with an influx of newcomers from those places (such as Phoenix and Miami). “

Read the full article here.

Source: IMF Working Paper (2022)

In this paper, the authors have developed a new measure of aggregate trade restrictions (MATR) using data from the IMF’s Annual Report on Exchange Arrangements and Exchange Restrictions. It covers an unbalanced panel of 157 countries annually between 1949 and 2019, and is correlated with existing measures of openness and trade policy.

“MATR aggregates the multitude of ways that countries restrict the international trade of goods and services. The underlying variables cover tariffs, non-tariff barriers, and restrictions on requiring, obtaining, and using foreign exchange for current transactions. More precisely, MATR is based on the IMF’s AREAER binary variables related to: (i) exchange measures; (ii) arrangements for payments and receipts; (iii) imports and imports payments; (iv) exports and exports proceeds; and (v) payment and proceeds from invisible transfers and current transfers.”

In the second half of the paper, they establish its efficiency as a measure by using it to investigate the aftermath of trade restrictions across parameters like region, time, income groups etc.