The Unassuming Economist

From VoxEU post by Paul Johnson and Chris Papageorgiou:

“The recent wave of growth in several developing economies has led to many analysts to claim that poorer countries are catching up with advanced economies. This column argues that, with the exception of a few countries in Asia which exhibited transformational growth, most of the economic achievements in developing economies have been the result of removing inefficiencies which are merely one-off level effects. While these effects are not unimportant and are necessary in the process of development, they do not imply ongoing economic growth.

In the past 50 years or so, the gap between average living standards in the poorest countries of the world and those in the richest countries has grown markedly. This unwelcome change is contrary to the proposition that less advanced economies ought to be able to catch up to more advanced economies through capital accumulation and technology transfer. Although the proposition wasn’t new, Abramowitz’s (1986) and Baumol’s (1986) examinations of its veracity as a negative correlation between initial per capita income levels and subsequent growth in per capita income, initiated a vast literature testing the so-called convergence hypothesis.¹ Following Barro and Sala-i-Martin (1990), the catch-up approach to the convergence hypothesis became known as β-convergence.²

Table 1 provides some insight into what has driven the widening gap between the poorest countries and the richest countries. It shows decadal average per capita GDP growth rates for low, upper-middle, and high-income countries (LICs, MICs, and HICs respectively) over the 50-year period from 1960 to 2010.

Table 1 Decadal average per capita GDP growth (%) by income

Notes: This table is an abridged version of Table 2 in Johnson and Papageorgiou (2018) where data sources and other details are given. There are 29 HICs, 68 MICs, and 51 LICs. Appendix Table A.1 in Johnson and Papageorgiou (2018) lists the countries in each group.

Despite the slowdown in their average growth rates over this period, the HICs have typically grown more quickly than the MICs, which in turn have grown more quickly than the LICs. These differences are the exact opposite of the pattern required for catching up to be observed, and so it is hardly a surprise that the dispersion of per capita GDP across countries has grown markedly since 1960. This growth is documented in Figure 1, which plots the standard deviation of the cross-country distribution of GDP per capita for a constant group of countries from 1960 to 2010 and shows that, apart from a small decline in the very late 2000s, the dispersion has risen steadily since 1960.

In addition to lagging that of the HICs and MICs, the growth experience of the poorest countries from 1960 to 2010 has been heterogeneous, both across countries and over time. Table 1 shows that the LICs experienced a continuous decline in growth rates in every decade from the 1960s to the 1990s, with negative growth rates in the 1980s and 1990s, before the surprising and unprecedented resurgence of growth in the 2000s. The MICs saw a similar resurgence in the 2000s although their slowing in the 1980s did not produce the negative growth rates experienced in the LICs.

Table 1 also makes the distinction between what are commonly called fragile and non-fragile LICs. Fragile states are those facing political frailty, characterised by weak institutional capacity, poor governance, corruption, and conflict. This distinction illuminates the marked differences in the growth experiences of the fragile LICs and the non-fragile of LICs, most notably in the 1990s and 2000s when the annual average growth rates differ by over 2 percentage points. That is, while there is a lot of optimism over the most recent growth acceleration in LICs, aggregating their experience masks the fact that only about half of the LICs are contributing to the resurgence while the rest are stagnant.”

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From a new INCLUDE report:

“While most African countries have registered high economic growth, a large number of people remain excluded from the benefits of this progress. INCLUDE envisages that inclusive development aims to reduce poverty, both in income and non-income dimensions, and inequality, through improved redistribution on these dimensions. Inclusive development is increasingly recognized as a must, since inequality is rising and the evidence base of the detrimental effect of high levels of inequality on economic growth and social and political stability is increasing. INCLUDE identified six policy domains that are key to reduce poverty and inequality:

• Economic growth with structural transformation of the economy.
• Productive employment; i.e. more jobs with good working conditions, remuneration and stability.
• Social protection for resilience, poverty reduction and sustainable economic growth.
• The provision of basic services (education, health, finance, infrastructure, housing, water, etc.).
• Territorial development and spatial equity (e.g. between rural and urban areas).
• Quality and inclusive governance, especially for poor minorities and other marginalized groups.

These policy domains are clearly interlinked and it is important to identify and empower strategic actors for effective and inclusive design and implementation of policies. Working with strategic actors and investing in these policy domains is however not sufficient. To move beyond pro-poor and pro-growth approaches towards inclusive approaches with more inclusive outcomes requires the consideration of three key areas:

• Equality: besides absolute improvements, policymakers should consider the distributional consequences of their policy choices. Evaluation mechanisms should therefore recognize the added
  value of reducing inequality.
• Diversity: considering distributional consequences helps to understand the heterogeneity in access to an realization of development outcomes. To move beyond the mere recognition of heterogeneity towards inclusive action, policymakers are encouraged to develop integrated policies where interventions complement each other to not only create improvements on average, but to also decrease inequality, even if this creates an ‘extra mile needed to reach the more difficult to reach.
• Context: to move beyond one-size-fits-all solutions, policies need to be aligned with local or regional contexts. Policies that fail to integrate with horizontal and vertical policy frameworks, and fail to identify and include strategic actors, are likely to promote exclusion rather than inclusion. “

A new paper “revisits the old standing issue of the stability of labour shares. […] Empirical results indicate diverse patterns in labour share movements, the most preponderant being a downward deterministic trend with break(s). Upward trends are observed in a limited set of economies (Belgium, Luxembourg and the Netherlands).  Overall, the stability of the labour share hypothesis appears to find only weak support. Exploratory analysis demonstrates that most of the structural breaks are economically significant and relate to the recent economic and political history of individual economies. The nature of labour share dynamics, as a country-specific and (to a large extent) policy and political phenomenon, is emphasized.”

From a VoxEU post by Ricardo Perez-Truglia:

“Tax records became easily accessible online in Norway in 2001, allowing everyone in the country to observe the incomes of everyone else. This column offers evidence that people primarily went online to snoop on the incomes of friends, relatives, and other contacts. This game of income comparisons negatively affected the wellbeing of poorer Norwegians while at the same time boosting the self-esteem of the rich.

Technological advances have made it possible for everyone to know potentially everything about everyone else. Sci-fi shows such as Netflix’s Black Mirror imagine dystopian scenarios that could result from these new technologies. In the real world, social media is already allowing individuals to disclose details about their personal lives with strangers. This technological change has sparked a policy debate too: should governments disclose data such as tax records?

Tax transparency in Norway

To understand how far reaching the societal consequences of transparency could be, it is useful to look at the experience of one of the pioneers of transparency, namely, Norway. Tax records have been public in Norway since the 19th century, but they have not always been easily accessible. Before 2001, an individual had to make a formal request in person at a tax agency to see someone else’s income. In the fall of 2001, the Norwegian media digitised tax records and created websites that allowed any individual with internet access to search the entire country’s tax records easily and effortlessly. Every Norwegian could find out the incomes of anyone else in the country in a matter of seconds.

In the following decade, Norwegians engaged in a heated debate about whether tax records should be easily accessible online. A similar debate took place in neighbouring Sweden, Iceland, and Finland. These other Scandinavian countries also had laws making tax records public, and thus had to decide whether to make them easily available online as in Norway.

There was no consensus among politicians or the general public on whether Norway’s transparency was good or bad. At its core, the disagreement was about what the effects of transparency actually are. Some supporters argued that public records could serve to deter corrupt politicians and tax evaders (Bø et al. 2015). Meanwhile, detractors claimed that the tax records would be used in objectionable ways, to snoop on the incomes of friends, for example. Thus far, only qualitative and anecdotal evidence has substantiated this contention. In a recent paper (Perez-Truglia 2019), I provide the first quantitative evidence on the matter.

Figure 1 shows a screenshot of one of the websites that allowed Norwegians to browse the tax records. These websites were easy to use and became incredibly popular in the country for the following decade. ”

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From a new IMF working paper:

“In this paper, we show that nighttime lights can be a useful source of information to improve official real GDP data. To begin with, they can be used to detect the uncertainty in official data and potential mismeasurement of real GDP. Systematic differences between the new and official measures may warrant further investigation as to what contributes to such differences. While nighttime lights can be computationally intensive to process, the method developed in this paper is not limited to nighttime lights. In fact, measures of real GDP that are conditionally independent of official data can be used in a similar fashion.”

“Figure 1 compares satellite images of nighttime lights for mainland China, […] Variation in nighttime lights may thus contain useful information on China’s real economic growth.”

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