nep-gro New Economics Papers
on Economic Growth
Issue of 2023‒08‒28
five papers chosen by
Marc Klemp, University of Copenhagen

  1. How does democracy cause growth? By Vanessa Boese-Schlosser; Markus Eberhardt
  2. Long Tails, Automation and Labor By B. N. Kausik
  3. Local Economic Growth and Infant Mortality By Andreas Kammerlander; Günther G. Schulze
  4. Measuring Economic Growth with a Fully Identified Three-Signal Model By Andrea Civelli; Arya Gaduh; Ahmed Sadek Yousuf
  5. Economic Growth and Pollution in different Political Regimes By Andreas Kammerlander

  1. By: Vanessa Boese-Schlosser; Markus Eberhardt
    Abstract: Recent empirical work has established that ‘democracy causes growth’. In this paper, we determine the underlying institutions which drive this relationship using data from the Varieties of Democracy project. We sketch how incentives and opportunities as well as the distribution of political power shaped by underlying institutions, in combination with the extent of the market, endogenously form an ‘economic blueprint for growth’, which likely differs across countries. We take our model to the data by adopting novel heterogeneous treatment effects estimators, which allow for non-parallel trends and selection into institutional change, and run horse races between underlying institutions. We find that freedom of expression, clean elections, and legislative executive constraints are the foremost drivers of long-run development. Erosion of these institutions, as witnessed recently in many countries, may jeopardise the perpetual growth effect of becoming a liberal democracy we establish for the post-WWII period.
    Keywords: Democracy, Growth, Institutions, Interactive Fixed Effects, Difference-in-Difference
    Date: 2023
  2. By: B. N. Kausik
    Abstract: A central question in economics is whether automation will displace human labor and diminish standards of living. Whilst prior works typically frame this question as a competition between human labor and machines, we frame it as a competition between human consumers and human suppliers. Specifically, we observe that human needs favor long tail distributions, i.e., a long list of niche items that are substantial in aggregate demand. In turn, the long tails are reflected in the goods and services that fulfill those needs. With this background, we propose a theoretical model of economic activity on a long tail distribution, where innovation in demand for new niche outputs competes with innovation in supply automation for mature outputs. Our model yields analytic expressions and asymptotes for the shares of automation and labor in terms of just four parameters: the rates of innovation in supply and demand, the exponent of the long tail distribution and an initial value. We validate the model via non-linear stochastic regression on historical US economic data with surprising accuracy.
    Date: 2023–07
  3. By: Andreas Kammerlander; Günther G. Schulze (Department of International Economic Policy, University of Freiburg)
    Abstract: We show, for the rst time, a causal eect of local economic growth on infant mortality. We use geo-referenced data for non-migrating mothers from 46 developing countries and 128 DHS survey rounds and combine it with nighttime luminosity data at a granular level. Using mother xed eects we show that an increase in local economic activity signicantly reduces the probability that the same mother loses a further child before its first birthday.
    Keywords: local economic growth, child mortality, nighttime lights
    JEL: I15 O18
    Date: 2021–09
  4. By: Andrea Civelli; Arya Gaduh; Ahmed Sadek Yousuf
    Abstract: We augment Henderson, Storeygard, and Weil (2012)'s two-signal model of true income growth with a third signal to overcome its underidentification problem. The additional moment conditions from the third signal help fully identify all model parameters without ad-hoc calibrations of the GDP's signal-to-noise ratio. We characterize the necessary properties of the third signal. Using the model, we recover the optimal weight of the GDP in the composite economic growth estimates, which varies with the quality of the national statistics and the geographic level of analysis. The model improves on existing methodologies that use signals to measure true income.
    JEL: E01 O11 O47 O57
    Date: 2023–07
  5. By: Andreas Kammerlander (Department of International Economic Policy, University of Freiburg)
    Abstract: I examine the association between nighttime light luminosity and ten pollution measures (CO2, CO, NOx, SO2, NMVOC, NH3, BC, OC, PM10 and PM2.5) across dierent political regimes at a local level. Although the eects of the political system and economic growth on pollution have been widely analyzed at the country level, this is the rst study to do so at the grid level. The empirical analysis yields three major insights. First, economic growth is positively associated with a wide array of dierent pollution measures. Second, there are signicant dierences in the association between economic growth and air pollution across dierent political regimes. For example, the association between nighttime light luminosity and air pollution is strictly positive for autocracies. The association between nighttime luminosity and air pollution is substantially smaller but still positive for democracies. Furthermore, among democracies the relationship between nighttime light luminosity and air pollution is concave for nine out of ten pollutants; among autocracies, the relationship is either convex (ve out of ten pollutants) or the squared term is insignicant. Third, the dierences among political regimes is driven chiey by pollution emissions in the industry, energy, and transport sectors; there is no dierence between autocracies and democracies in terms of the eect of growth on emissions in the agricultural and residential sectors.
    Keywords: local economic growth, air pollution, nighttime lights, geo-data
    JEL: O18 Q53
    Date: 2022–10

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