Can Land Reform Avoid a Left Turn? Evidence from Chile after the Cuban Revolution

More than 3 million hectares were expropriated from the hands of landowners before that date, which accounts for approximately 12.5% of Chile’s main agricultural area (the so-called “center valley,” regions IV to X, see Figure A.1). This is big when compared to the 310 thousand hectares expropriated in Venezuela by 1973 and the 135 thousand hectares expropriated in Colombia by 1969, which represents 0.33% and 0.12% of each territory, respectively (Oliart and Araujo 1974).

There are better identification strategies to estimate the causal effect of a redistributive policy (typically government transfers) on political support for the incumbent (e.g. Pop-Eleches and Pop-Eleches 2010; Manacorda Miguel, and Vigortio 2011). This is mainly because they rely on more plausible identification assumptions by exploiting a manipulated regression discontinuity design.

See Kramer (1971), Stigler (1973), Fair (1978), Hibbs (2006) and Cerda and Vergara (2007) for the former literature and Levitt and Snyder (1997), Schady (2000), Manacorda, Miguel, and Vigortio (2011), Pop-Eleches and Pop-Eleches (2010) for the latter.

See Dube, Kalpan and Naidu (2011), Berger et al. (forthcoming) and Nunn and Qian (2012) for examples. To the best of my knowledge, the hypothesis that motivates this research, i.e. that land reform had political effects, is entirely original. Therefore, there are no prior beliefs among historians or economists about the potential answers to this question for the Chilean case.

As McBride (1970) puts it: “Chile’s social structure was built on land bases, and the entire life of the nation had to be shaped in relation to land (...) The condition of each person was determined by the ownership or not ownership of an hacienda.”

Indeed, Conning and Robinson (2007) calculate that land gini coeffient in Chile was about 0.94 in 1965. Other land gini coefficients are: Argentina 0.79, Brazil 0.84, Bolivia 0.94, Bangladesh 0.42, India 0.62, France 0.54, and United States 0.73. Many historians hypothesized that this high land concentration has its origins in colonial times (e.g. Bauer 1975 and Baraona 1960).

Flores (1963) puts it clearly: “Fidel Castro has claimed to be the indirect promoter of the Alianza [Alliance for Progress]; and there is some truth in his boast, since without the Cuban Revolution Latin America would not be in the headlines today (...) Without Castro, few outside Latin America would care about the region’s economic stagnation [and] its political instability.”

Taffet (2007) succinctly says: “new policies were necessary because the successes of the Cuban Revolution suggested that the entire region was vulnerable to communism.”

Chile went from being a net exporter of agricultural products in the 1930s, to a growing trade deficit at the beginning of the 1960s. Indeed, during years 1936–1938, there was a trade surplus in agricultural products of 1.1 million US dollars, while in 1963 the annual deficit was around 124 million US dollars (Chonchol 1976).

Huerta (1989) offers a good description of this process: “There is a total resistance to an structural Agrarian Reform before the fifties. The reason is clear, it implies transmission of power, social modifications, and more political participation. Even though the agrarian problem start as an economic issue, it soon transformed into a political problem (...) Agricultural workers have been absent as participants of the national problems, they do not have means of expression.”

The main objectives of this law were to give access to land to agricultural workers, to im-prove the living standards of the rural population, and to increase agricultural production and soil productivity (Law 15.020 art. 3, Diario Oficial N.25, November 27, 1962).

The general agreement about the need for a more intense land reform was reflected in the 94% approval rating at the Congress (Barraclough 1971).

In fact, several historians refer to these agrarian reform period of Jorge Alessandri as “Reforma de Macetero” (Pot Reform), in direct reference to the small amount of reformed land (e.g. Correa et al. 2001).

This political migration of the Radicals between 1958 and 1970 is fairly well documented by Collier and Sater (2004).

This pattern is clear for both the 1958 and the 1970 presidential elections (see Table 2) as well as in other elections (see Table 1). The exception is the 1964 presidential election and the 1961 parliamentary election due to the alliance of the right wing with the center due to the threat of a potential Marxist government.

Wright (2000) is an exception and argues that the revolution was indeed something desired by the majority of Latin Americans; thus, it was an immediate precedent for the guerrillas and revolutions that came after it.

As we will see, the period 1964–1970 was the most intense period of land reform and we could use the 1964 presidential election as the election before land reform implementation. However, a political episode known as “Naranjazo” greatly affected the actions of the right wing and they joined the center in order to avoid a potential government of Salvador Allende.

Descriptive statistics for auxiliary variables are presented in Table A.2 in the Appendix. Aux-iliary variables are defined as (i) secondary controls and (ii) those used in the robustness checks.

See Figure 2 for a graphical analysis of land reform heterogeneity at the municipal level. A bar represents the percentage of land expropriated in each of the 210 municipalities. Results are robust if I use (i) expropriation divided by agricultural surface instead of total surface and (ii) the amount of land expropriated only under the government of the Christian Democrat Eduardo Frei.

The change in the percentage of agricultural workers is probably not accurate, as the increase from 21% to 51% seems somehow implausible. This is probably because the 1960 and the 1970 IPUMS sample did not targeted representation of different labor forces. However, this is not a problem for this particular paper because I am not comparing the change in the level of the share in the same municipality but rather across municipalities.

The average number of cars and the percentage of houses with television and radio are ob-viously a crude proxy of income. However, to the best of my knowledge, there are not any other measures of income at the municipality level for this period.

Land concentration is constructed with information from the 1955 Agricultural Census. This information is at the municipality level, but we know how many plots there are in each municipality and what is their approximate size (12 categories, in physical hectares). Therefore, we can construct a land gini coefficient. This coefficient equals 0 if all physical hectares in the municipality are equally divided among its entire population, and equals 1 if one person is the owner of all physical hectares.

Nevertheless, there seems to be a statistically significant correlation between land reform and political support for the Radical Party: a one standard deviation increase (0.10) decreases land reform by 0.02 (–0.19×0.10, 0.12 standard deviations). If there is some political targeting, the Christian Democratic Party seems to have targeted radical voters, either intentionally or unintentionally.

Indirectly, this empirical analysis documents a well-known stylized fact: a political migration of voters from the Christian Democratic Party (political center) to the left and right wing. This occurred after the peak of the Christian Democrats in the middle of the sixties, where they reach a political support of more than 50%.

Alternatively, I could have used a panel dataset including the 1964 presidential election. However, I prefer this empirical strategy because (i) the instrument I use only varies between municipalities, (ii) there is no data for the control variables in 1964, thus I would have to use linear interpolations, and (iii) there is no candidate from the Right Wing Party in 1964. Nevertheless, results do not change using this alternative strategy (results available upon request).

There are other empirical strategies I could have used. For example: (i) Conley (1999) spatial standard errors and (ii) the same dummy in eq. [1] weighted by the distance to a municipality with land reform. Qualitative and quantitative similar results are obtained with both strategies.

The covariate Δ rurality also helps to control for internal rural-urban migration, which seems to be changing in a different way during the sixties (Herrick 1966, and Cerrutti and Bertoncello 2003).

It is not straightforward to compare coefficients and. We need to multiply these coeffi-cients by the standard deviation of land reform and neighbor to be able to compare them.

The variable land reform is normalized in order facilitate the interpretation of. Thus, the coefficient of interest indicates the change, in percentage points, in the corresponding dependent variable.

A one standard deviation increase (0.486) increases political support for the Political Center by 0.5 percentage points (0.486 × 0.011). In all specifications hereafter, the effect is larger based on the closeness of the neighbor municipalities, but never as bigger as the direct effect, and zero when they are far away from each other. I use centroids to calculate distances. Results not shown for parsimony but available upon request.

The first two are valid concerns, but the last one is not because only 12 out of the 5,422 expropriations have missing date of expropriation and, thus, are missing in the data set. Among these, only six were bigger than 100 physical hectares.

Bauer (1975), for example, states that “From the 17th century there was a tendency to have large haciendas, and these were notably stable until the nineteenth century.” The translation is mine.

Next subsection provides evidence supporting this assumption. Figure 3 shows the persis-tence of land concentration at the municipality level by plotting the logarithm of total exploitations at the municipality level in 1920 and in 1955. The main idea is that, because a municipality’s territory is constant over time, a persistent land concentration should be translated into a positive correlation between the number of plots with agricultural activities in two different points in time.

This suggests an absence of a weak instrument problem (Hahn and Hausman, 2003) according to the statistical tables in Stock, Wright, and Yogo (2002).

An exploitation is a plot with agricultural activities. The 1920 variable is therefore interpreted as a proxy for number of exploitations. This variable also incorporates landowners in the urban areas and it is only available for 172 municipalities out of the 210. However, it is the best available measure for land concentration at the municipality level before 1955. To the best of my knowledge there are no other measures at the municipality level prior to this period.

Ideally I would like to look at the change in the CDP vote share between the 1952 and 1958 presidential elections. However, there is not clear distinction of left, center, and right wing and the CDP did not exist in 1952. This is why I use non-left wing and parliamentary elections in 1953 and 1961. This non-left wing is called Falange Nacional and is actually the main political force from the center of the political spectrum during the 1950s.

I use non-left here because at the 1964 presidential elections, the right and the political center were represented by only one candidate. This happened mostly due to the fear of the right wing of a left wing government (Collier and Sater 2004). See Table 1 for details.

When θ_k ≠ 0 a violation to perfect exogeneity has taken place. Until now I have assumed that θ_k = 0, but it is not a testable assumption.

A local to zero approach, i.e. but , results in a and a confidence interval of [0.137, 0.782] (without normalization). Using different support assumptions for Θ, with, I find out that θ₀ must be in order to have a zero effect of land reform on voting patters. I argue that because this is a large effect this provides further evidence for the IV approach.

Regions are historically named by a roman number: region I, II, III, and so on until region XII. The exception is the metropolitan region (MR), the capital. My analysis is on the geographic area named Central Valley, were regions IV, V, VI, VII, VIII, IX, X, and MR are located.

Provinces are administrative units bigger than municipalities but smaller than regions. Cur-rently, there are 15 regions, 54 provinces, and 345 municipalities in Chile.

The main de jure objective at this stage was to: (i) efficiently exploit the expropriated land, (ii) prepare peasants to assume their responsibilities as owners and agricultural entrepreneurs, (iii) guide and promote the community’s development, (iv) promote agricultural activities as the main source of income among peasants, (v) build the minimum infrastructure necessary for the exploitation of the plot.

I would like to thank an anonymous referee for mentioning this potential mechanism.

However, empirical support for this theory is mixed, with some studies finding positive and other modest or insignificant results. The empirical evidence is equally mixed in the United States, Western Europe, and developing countries. See Pop-Eleches and Pop-Eleches (2010) for a review.

Leigh (2006) tries to disentangle socioeconomic and unions effects with panel data and finds evidence of a union-effect. However, the author does not explain why this pattern is found.

However, Freeman (2003) is not able to disentangle the voting effects of being unionized from just being different in socio-economic aspects, because workers in unions are different from those who are not.

There is research arguing that agricultural workers and rural areas voted relatively more for the Christian Democratic Party (e.g. Petras and Zeitlin 1968, 1970)

Higher support for the Christian Democrats is defined as those municipalities with more than 17% of votes (the median) for Eduardo Frei in the 1958 presidential election. Results are robust to different definitions.