# Melissa Dell and Benjamin Olken (REStud, 2020). The development effects of the extractive colonial economy: The Dutch Cultivation System in Java.

I didn’t want to leave this space untouched for too long, so I thought I would squeeze in a quick post before my last final of this semester (and my undergraduate candidature in NUS!)

I summarize a paper by Melissa Dell, 2020 JBC medal winner, in this post. Since this is a summary, I do not cover everything in the paper, and do not describe the robustness checks performed. If you are curious about the details, the paper can be found here.

Research Question

Acemoglu and Robinson’s (2012) Why Nations Fail (a debater starter pack book) drew vivid contrasts between different case studies, reifying that economic and political institutions are instrumental determinants of economic growth. Across almost all countries in Southeast Asia, many of these key institutions are transplants, kept intact even as the sun set on the age of empire. Have these institutions hurt or helped economic development? In Singapore, the Bicentennial last year reinvigorated heated debate about this.

Dell and Olken’s (2020) paper answers this question in the context of Java, Indonesia. Java came under Dutch rule in 1800. In 1830, as Dutch historian Cees Fasseur (1986) writes, Dutch Governor-General Johannes van den Bosch established the cultuurstelsel, or Cultivation System. This was a system that coerced the Javanese into agricultural activity (most predominantly, sugar cultivation) to enrich the Dutch government.

Perhaps useful TL;DR and disclaimer here: the Cultivation System instituted by the Dutch did bring about a net economic gain, but Olken highlights that these results should not be taken as representing that Dutch colonial rule was a net positive for Indonesia. Indeed, there are several problems with this interpretation of the study. A comprehensive cost-benefit analysis must also take into account the costs suffered by subjugated locals, the social costs of enduring myths about the native population, the use of anti-colonial rhetoric to mobilize the masses to vote for economic policies that actually work against them, alongside other factors. All of these fall outside the scope of this study.

The Cultivation System, as the paper lays out, could have affected the development trajectory of Java, and specifically the sugar cultivation villages, through four causal mechanisms, summarized below.

Sources of data

To study whether a positive or negative effect on economic growth dominates, the paper uses historical data on the Cultivation System from manuscript archival records, and 1900 infrastructure maps published by the Dutch Topographic Bureau. The manuscript archival records contain information on which villages contributed to each sugar factory and the contribution (in terms of land and labor) of each village. In total, by geographical coordinate matching, 6,383 historical villages were able to be mapped to the 2,519 modern villages that now occupy these territories. Factories were mapped in this way as well. Data on modern growth and growth-related outcomes were obtained from the Indonesian government’s Central Bureau of Statistics (BPS) datasets.

Empirical strategy

Effects of proximity to a sugar processing plant

To determine whether being in close proximity to a sugar processing factory had an effect on economic development, Dell and Olken (2020) compared the outcomes of villages near actual old sugar processing factories to the outcomes of villages near counterfactual sugar processing factories (i.e. locations that would have been suitable for sugar processing factories to be built, but where sugar processing factories were not built because they would have been located too near another sugar processing factory and ate into its catchment area).

They constructed counterfactual factory locations based on three criteria:

1. Counterfactual location must be within 5 to 20 kilometres upstream or downstream from the actual factory location
2. Counterfactual location must have as much land suitable for sugar cultivation (determined by slope, elevation) within a 5 kilometre radius as the 10th percentile of the distribution of actual locations
3. Counterfactual locations must be spaced as far apart as actual factories within the 10th percentile of the distribution

The specification for the regression ran was as such:

$out_{v} = \alpha + \sum_{i=1}^{20} \gamma_{i} dfact_{v}^{i} + \beta X_{v} + \sum_{j=1}^{n}fact_{j}^{v} + \epsilon_{v}$

• $out_{v}$ is the outcome variable of interest for the village
• $\sum_{i=1}^{20}\gamma_{i} dfact_{v}^{i} = \gamma_{1}(dfact_{v}^{1} + \gamma_{2}dfact_{v}^{2} + \gamma_{3}dfact_{v}^{3} + ... \gamma_{20}dfact_{v}^{20}$, where $dfact_{v}^{1}$ is a dummy variable indicating whether the village is located within a 0-1 kilometre radius of the nearest factory (and $\gamma_{1}$ is obviously the coefficient on this term), $dfact_{v}^{2}$ is a dummy variable indicating whether the village is located within a 1-2 kilometre radius of the nearest factory, and so on
• $X_{v}$ is a set of controls, including variables like elevation, slope, etc.
• $\sum_{j=1}^{n}fact_{j}^{v}$ are nearest factory fixed effects, to compare each village to villages near the same sugar processing factory (shown in the below diagram)

Effects on villages made to grow sugar cane

To study the effect of the Cultivation System on the villages coerced into sugar cultivation (“subjected villages”), Dell and Olken (2020) further used a regression discontinuity design, exploiting the discontinuity at the boundaries of catchment areas made to grow sugar cane. Within these boundaries, villages were made to grow sugar cane; outside them, villages were not. The sample under analysis comprises only villages that had arable land suitable for the cultivation of sugar then.

$out_{v} = \alpha + \gamma cultivation_{v} + f(geographic$ $location_{v}) + g(dfact_{v}) + \beta X_{v} + \sum_{i=1}^{n}seg_{v}^{i} + \epsilon_{v}$

• $out_{v}$ is, as mentioned above, the outcome variable for each village
• $cultivation_{v}$ is a dummy variable taking the value of 1 if the village grew sugar cane under the Cultivation System (“subjected”), and 0 otherwise
• $f(geographic$ $location_{v})$ is the regression discontinuity polynomial, which is estimated separately for each catchment area
• $g(dfact_{v})$ controls for distance from a sugar processing factory, in order to isolate the effect of being made to cultivate sugar from that of being located near a sugar processing factory
• $seg_{v}^{i}$ are the fixed effects such that villages are compared to other villages nearest to them (i.e. in the same segment of the catchment area)

Main findings

Effects of proximity to sugar processing factory

Economic structure

Living in a village within a few kilometres of a historical factory is associated with a 20 to 25 percentage point decrease in the likelihood of working in agriculture, relative to living in a village 10 to 20 kilometres away from such a historical factory. Moreover, living near an actual historical factory is associated with a 17 percentage point decrease in the likelihood of working in agriculture, relative to living near a counterfactual historical factory.

Sugar-related industrial activity

Even after limiting the sample to historical sugar processing factories that are not near modern sugar processing factories, being within 0 to 1 kilometre of a historical factory is associated with an increase in employment in manufacturing industries downstream from sugar (food processing plants that use sugar as an ingredient, etc.). This may reveal that agglomeration effects are an important contributor to the continuity of industrial activity in these areas: manufacturing companies downstream from sugar still have an incentive to locate near historical factories because of potential cost savings arising from many factories in the same or related industries located there.

Public good provision

Being located in the immediate vicinity of a historical factory is associated with an increase in the likelihood of having a local high school as well as having electricity. This may be due to the greater accessibility of these places (being located in the immediate vicinity of a historical factory is associated with higher road and rail density), greater village lobbying power due to being more industrialized, or local governments having a greater incentive to invest in distributing public goods to these areas as the returns on such investment in industrialized areas are higher.

Household consumption

Being located in the immediate vicinity of a historical factory is associated with an increase in household consumption. This increase may be attributed to an average 1.25 years increase in schooling from being located near a historical factory.

Effects on villages made to grow sugar cane

Economic structure

Individuals in subjected villages have a 15% decreased likelihood of being employed in agriculture, 14% increased likelihood of being employed in manufacturing, and 7% increased likelihood of being employed in retail.

Education

Based on data in the 2000 Population Census, individuals in subjected villages have approximately 0.24 years more schooling, relative to a sample mean of 5 years. They are also more likely to complete primary school and junior high.

Land ownership

In 1980 and 2003, village census collected information on village-owned land. In both years, it was found that subjected villages owned more land (approximately 1.4 percentage points more in 2003, relative to a sample mean of 9%, and approximately 1.2% more in 1980, relative to a sample mean of 11%).

Conclusion

The Dutch Cultivation System improved economic growth prospects for the areas near sugar processing factories and villages that were subjected. There are persistent changes in economic structure, public good provision, years of education, and land ownership in these places.

I have four more days before my final paper, after which I can get back to more frequent posts. I have a few posts in draft, so do visit this space again soon for my next update!