DYNAMICS AND STAGNATION IN THE MALTHUSIAN EPOCH PDF

Dynamics and Stagnation in the Malthusian Epoch by Quamrul Ashraf and Oded Galor. Published in volume , issue 5, pages of American Economic. This paper empirically tests the predictions of the Malthusian theory with respect to both population dynamics and income per capita stagnation. This paper examines the central hypothesis of the influential Malthusian theory, according to which improvements in the technological environment during the.

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Support Center Support Center. In the second period of life parenthoodtthey inelastically supply their labor, generating an income that is equal to the output per worker, y twhich they allocate between their own consumption and that of their children.

DYNAMICS AND STAGNATION IN THE MALTHUSIAN EPOCH

Columns 1—2 reveal the full-sample regression results for population density in the years CE and 1 CE. Consistent with Malthusian predictions, the analysis uncovers statistically significant positive effects of land productivity and the technological level on population density in the years CE, CE and 1 CE.

Thus, for instance, while statistical significance remains unaffected across specifications, the independent effects of Neolithic transition timing and land productivity from the first two columns in each table increase slightly in magnitude when both channels are examined concurrently in Column 3, and remain stable thereafter when subjected to the additional geographical controls in the baseline regression specification of the fourth column. These results are shown to be robust jalthusian controls for other geographical factors, including absolute latitude, access to waterways, distance to the nearest technological frontier, the percentage of land dtnamics tropical versus temperate climatic zones, and small island and landlocked dummies, all of which may have had an impact on aggregate productivity either directly, by affecting the productivity of land, or indirectly by affecting trade and the diffusion of technologies.

For each time period examined, the regressions for income per capita and population density reveal, exploiting identical variations in explanatory variables, that the estimated elasticity of population density with respect to the degree of technological sophistication is not only highly statistically significant, but at least an order of magnitude larger than the corresponding elasticity of income per capita.

For instance, the coefficient estimates for the year CE, all of which are statistically significant at the 1 percent level, indicate that a 1 percent increase in the number of years elapsed since the onset of the Neolithic Revolution is associated with an increase in the level of technological advancement in the communications, industrial, and transportation sectors by 0.

In every period, the economy produces a single homogeneous good using land and labor as inputs. Log Income stagnqtion Capita in: Summary — This figure depicts, using the income per capita data-restricted samplethe partial regression line for the effect of transition timing land productivity on population density in the year CE, while controlling for the influence of land productivity transition timingabsolute latitude, access to waterways, and continental fixed effects.

Finally, given the possibility that the disturbance terms in the baseline regression models may be non-spherical malthusia nature, particularly since economic development has been spatially clustered in certain regions of the world, the appendix presents results from repeating the baseline analyses for population density and income per capita in the three historical periods, with the standard errors of the point estimates corrected for spatial autocorrelation following the methodology of Timothy G.

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DYNAMICS AND STAGNATION IN THE MALTHUSIAN EPOCH

Finally, given the possibility that the disturbance terms in the baseline regression models may be non-spherical in nature, particularly since economic development has been spatially clustered in certain regions of the world, Tables D. Is your work missing from RePEc?

According to the Malthusian theory, on the other hand, not only will the long-run level of income per capita remain unaffected in the region undergoing technological advancement, it will remain unaffected in all regions as well.

Author information Copyright and License information Disclaimer. In particular, for a given time period and for a given culture in the archaeological record, the Atlas of Cultural Evolution draws on various anthropological and historical sources to report the level of technological advancement, on a 3-point scale, in each of four sectors of the economy, including communications, industry i. Please review our privacy policy.

Thus, Kremer does not test the absence of a long-run effect of the technological environment on income per capita nor does he examine the positive effect of technology on population size.

Specifically, the technology-diffusion hypothesis suggests that spatial proximity to societies at the world technology frontier confers a beneficial effect on development by facilitating the diffusion of new technologies from the frontier through trade as well as sociocultural and geopolitical influences.

Log Land Productivity 0. Despite differences in the estimated elasticities between the two periods, the similarity of the effects at the sample means arises due to counteracting differences in the sample means themselves. The effects of these explanatory channels on income per capita in the corresponding periods, however, are not significantly different from zero, a result that fully complies with Malthusian priors.

On the contrary, using a first-difference estimation strategy with a lagged explanatory variable, the analysis demonstrates that, while changes in the level of technology between BCE and 1 CE were indeed associated with significant changes in population density over the 1— CE time horizon, the level of income per capita across regions during this period was, in fact, largely unaffected, as suggested by the Malthusian theory. Summary — This table demonstrates that the timing of the Neolithic Revolution is positively and significantly correlated with the level of technology in multiple non-agricultural sectors of an economy in the years CE and 1 CE.

Population Growth and Technological Change: First, it establishes that the onset of the Neolithic Revolution, which marked the transition of societies from hunting and gathering to agriculture as early as 10, years ago, triggered a sequence of technological advancements that had a significant effect on the level of technology in the Middle Ages. The incorporation of parental cost for non-surviving children would not affect the qualitative predictions of the model. Members of generation t allocate their income optimally between consumption and child rearing, so as to maximize their intertemporal utility function 3 subject to the budget constraint 4.

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This section establishes that the Neolithic Revolution triggered a cumulative process of economic development, conferring a developmental head start to societies that experienced the agricultural transition earlier.

The analysis now turns to address issues regarding causality, particularly with respect to the transition-timing variable. Summary — This table establishes, consistently with Malthusian predictions, the significant positive effects of land productivity and the level of technological advancement, as proxied by the timing of the Neolithic Revolution, on population density in the year CE, while controlling for access to navigable waterways, absolute latitude, and unobserved continental fixed effects.

In comparison to the relevant baseline regressions presented in Columns 1 and 4 of Table 5the coefficients associated with the transition-timing and land-productivity channels remain both qualitatively and quantitatively stable. Plants and Animals used as instrumental variables The number of domesticable species of plants and animals, respectively, that were prehistorically native to the continent or landmass to which a country belongs. Trade and the Great Divergence: The remainder of the analysis in this section is concerned with establishing the causal effect of technology on population density in the years CE and 1 CE.

Results not shown from estimating these augmented first-difference specifications, however, are qualitatively similar to those obtained from estimating equations 17 and Census Bureau finds that their aggregate estimates indeed compare favorably with those obtained from other studies.

As before, the independent and combined explanatory powers of the transition-timing and land-productivity channels are examined while controlling for other geographical factors and unobserved continental characteristics. Similarly, in the income per capita data-restricted samples employed in Section 4. Thus, in line with the predictions of the Malthusian theory, the results indicate that, during the agricultural stage of development, temporary gains due to improvements in the technological environment were indeed channeled into population growth, thereby leading more technologically advanced societies to sustain higher population densities.

Regression 4 corresponds to the first stage of both regressions 3 and 6 in Table 8. Non-agricultural Technology Index in BCE, 1 CE, and CE The index of non-agricultural technology for a given year is based on the same underlying data and aggregation methodology discussed above for the overall technology index. However, unlike the overall index, the non-agricultural counterpart incorporates data on the sector-specific technology indices for only the communications, industrial i.

The current investigation therefore performs a rigorous robustness analysis of the baseline results with respect to the aforementioned data quality concerns. In the communications sector, the index is assigned a value of 0 under the absence of both true writing and mnemonic or non-written records, a value of 1 under the presence of only mnemonic or non-written records, and a value of 2 under the presence of both.

Insights from Unified Growth Theory. Population, Food, and Knowledge: