Research proposal of Sierra Leone

Research proposal for gender and ownership of property, land and other local resources within urban and rural communities in Sierra Leone
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Research Proposal For Gender And Ownership of Property, Land and Other Local Resources within Urban and Rural Communities in Sierra Leone
Nowadays Sierra Leone is facing and experiencing a lot of changes and reforms, dedicated to various spheres of human life and adjusted to challenges, created by the current situation in the world. In order to keep pace with them and ensure our society, that we consider pressing economic points from different prospects and find complex solutions, we’ve studying gender and ownership of property issue, as well as land and other local resources using, resorting statistics and econometric tools.

Conducting this research, we figure out actual level of social inequality, concerning male and female property and how the situation with allotment looks now. What is already known, what percentage of property holders among men is twice as large as among women? It can be explained by the traditional approach towards the legacy social position of the woman, as the dependent member of the family. But such explanation looks quite shallow and therefore we have to continue our research in order to understand general economic and mental motives and how they shift in another political and social (in our case- urban vs rural) environment.

As the situation with dramatic inequality is clear and can’t be doubted, another aim of the research is to estimate its consequences for the economy of Sierra Leone, what benefits and risks the reform can bring, what challenges will the government face, trying to put it into effect. Using statistics and econometrical tools the research group appreciates the necessity of the Three gender act and its influence on the crucial economic indicators, foresight advantages and disadvantages, peculiarities of implementation and compares them with previous experience of the states, which have already overcome such problem.

Another important task to fulfill is making the prediction concerning not only economic but also social consequences of the reform. Taking into consideration the traditional nature of society in Sierra Leone and its strong rural representation, which not always can share such modern tendencies, as women’s independency and ability to own and dispose of. But taking into consideration demographical indicators, increasing role of women in different political, scientific and cultural spheres in Sierra Leone and the fact the even the youngest generation in our country suffered from atrocities and humiliation, made during the War 1991-2002, we can be sure, that previous mechanisms of ownership and business relations in the state cannot satisfy new situation. That’s why, our research is focused not only on the economic statistics and GDP-indicators but also on the social and cultural terms. Only complex approach can provide successful implementation of reforms.

The first method to be used in our research is the check of the statistical massive of the amounts of land owned by men and women in Sierra Leone by men and women both for rural and urban areas using the normal distribution.
The normal law of distribution (also called Gaussian law) plays an extremely important role in probability theory and takes a special state among other distribution laws. This is a law that is often found in practice. The main feature that distinguishes a normal law among other laws is that it is the limiting law to which other distribution laws approach.
So, for example, a large number of cannon shots committed in various conditions, shows that the scattering of projectiles in the plane when firing from one gun with a specified scope is subject to normal law. The “universality” of the normal law is explained by the fact that any random variable, which is the sum of a large number of individual numerical values, each of which obeys different distribution laws and slightly affects the amount, is distributed almost according to the normal law.
Most of the random variables, such as, for example, measurement errors, cannon-gun shooting errors, etc. can be represented as the sum of a large number of small terms? elementary errors, each of which is determined by the action of an individual cause, does not depend on others. What division laws did not obey individual elementary errors, the features of these distributions in the sum of a large number of terms are leveled and the sum obeys a law close to normal. Summed up the errors in the total amount should play a relatively small role (Berk, 1983, 390).
In our research we assume that the ownership of land in different gender and urban/rural groups is redistributed normally. Thus the difference between the peaks of men-women, rural-urban and other statistical Gaussian bells will show the current state of inequality in the country. This difference in different regions of the country may be expressed in a coefficient and than be used in further research.
The second method is the analysis of correlations between the men-women and rural-urban inequality indexes in different regions and the value of Gross Regional Product per capita. Correlation expresses such a form of connection when a certain value of one value corresponds to a series of distribution of values ​​of another magnitude. Since the correlation dependence for each X corresponds to a whole series of values ​​of Y, they form in the coordinate system a certain “correlation field” of the quantity. For example, higher qualification of employees corresponds to a higher salary, although among them there may be people with different salaries. Work conditions and job satisfaction, parental education and performance of children, length of service and labor productivity are correlated. The presence of correlation indicates that, either one of the isolated phenomena is a partial cause of the other, or both phenomena are a consequence of common causes. But revealing a correlation does not give grounds for asserting a causal relationship of phenomena. So, Shubkin found a correlation between the salary of parents and the achievement of their children – schoolchildren; Richardson found it between the salary of teachers and the consumption of wines in the US. In the first case, the correlation is explained by the fact that, as a rule, more educated parents received a higher salary, and in the second – by the fact that during this period (1870-1910) the salary in the USA (including teachers) and accordingly, the consumption of food products (including wine) increased, that is, teachers’ salaries and wine consumption were the result of common causes, and not cause and effect in relation to each other (Ballock et al., 1975, 83).
Even though correlation is not the most precise instrument it still shows important interconnections between the issues of gender and rural inequality and the relatively low economic development of the country.
Indicators reflecting the measure of correlation (tightness, the direction of communication) are called correlation coefficients. In sociology, the Yule coefficient (Q), the two-way coupling coefficient (P), Pearson (R), Spearman rank correlation, the multiple correlation coefficients (W), the Chuprov coefficient (T) and Cramer (K) are used. In our research, we are going to use Pearson correlation as it represents the interrelations between the trends and thus do not require the single dimension of the coefficients established in the previous part of the research.

The final stage of our research is building econometric models on the basis of the collected data to foresee the social and economic effects of the “Three Gender Acts” onto the level of economic development of the country. The econometric model is a statistical model that is a means of predicting the values ​​of certain variables, called endogenous variables (endogenous variables dependent). In order to make such forecasts, the values ​​of other variables, called exogenous variables (exogenous variables independent), are used as initial data. The econometric model can be a very complex system and a simple formula that can be easily calculated on a calculator. In any case, it requires knowledge of economics and statistics. First, knowledge of economics is used to determine the corresponding relationships, and then to evaluate the quantitative nature of the relationships, the data received over the past period is processed using statistical methods (Clogg et al., 1995, 224).
The simplest relationship between the two variables is a linear relationship between them, which is described by a linear function and is called simple linear regression.
 Y=b0+b1X+e . (1.1)
where Y is the resultant or dependent variable, X is the explanatory variable, e is the random variable (perturbation), b0, b1 are the unknown parameters of the model. Thus, the dependent variable Y is represented as the sum of deterministic (b0+b1X) and random (e) components and is random (whereas X is assumed to be deterministic).
The true values ​​of parameters b0 and b1 can not be calculated since a limited number of observations are usually available to the researcher, so unknown regression parameters are subject to evaluation by a certain procedure. We will denote the estimates of the parameters by b0 and b1, respectively. Then the pair regression equation

 Y’=b0+b1X (1.2)
will be an estimate of the model (1.1).
In this equation, b0 is the regression constant (free term). It can be represented as a coefficient with a dummy variable identically equal to 1.
The dependable variable in our model is per capita GRP, while the variable is rural men-women inequality coefficient studied in the previous two stages. The suggestion is the gradual decrease of inequality coefficient after the reform and thus increasing the economic effect. The simple model may be complemented with the variable of the amount of rural population in different regions showing more interconnection with the land and farming.

The main source of data for our research are agricultural and poverty profiles of Sierra Leone, prepared by the World Bank and the National Statistical Office Sierra Leone. The key issues in the methodology are the reliability of the data provided as the country has the rather weak statistical infrastructure and the actual state of data as most of the publications are of the 2012-2013 and thus are 3-4 years old. However as all of our methods provide for relative and not absolute values, in general, they may somehow disregard the issue of resources outdated unless any dramatic changes occurred in the social pattern of the country (National Statistical Office Sierra Leone, 2017, n.p.; The World Bank, 2011, 5; The World Bank, 2014, 7).
References
Ballock, Raymond et al., 1975. Quantitative sociology: international perspectives on mathematical and statistical modeling. New York, Academic Press Inc.
Berk, Richard, 1983. An Introduction to Sample Selection Bias in Sociological Data, American Sociological Review Vol. 48, No. 3, pp. 386-398
Clogg, Clifford, et al. 1995. Statistical Methods for Comparing Regression Coefficients Between Models, American Journal of Sociology, Volume 100, Number 5, 214-231
National Statistical Office Sierra Leone, 2017. “Sierra Leone Integrated Household studies,” Sierra Leone Statistics. [Online] Available at: https://www.statistics.sl/ [14 January 2018]
The World Bank, 2014. AGRICULTURAL PROFILE FOR SIERRA LEONE. Washington, The World Bank
The World Bank, 2011. POVERTY PROFILE FOR SIERRA LEONE. Washington, The World Bank