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Informed Consent Form Essay The purpose of this research is to study the attitude of males towards police on campus. You will be asked questions which might make some people feel uncomfortable, while it may be pleasant for others. Should you wish to withdraw your participation you are free to do so at any time. The identity of participants will remain strictly confidential. It will be masked in all written reports and transcripts of tapes. All interviews will be taped and transcribed and only the investigator will have access to the tapes. After six months from the date of the interview each tape will be erased. This research project will not be published. I have read the above description of this research project and have a satisfactory understanding of what my participation will involve. The investigator has answered my questions regarding this project. I consent to take part in this investigation. If you have further questions regarding this research please feel free to contact (Your name) (Investigator) at (209) 830-9284.

Effect of Remittances on Household Consumption Patterns

Effect of Remittances on Household Consumption Patterns Do remittances affect the consumption pattern of the Filipino households? Objectives The objective of this paper is to formulate structural models to illustrate the change in consumption pattern of the Filipino households. In this study, our aim is to use an advanced econometric approach to find out if there is indeed such change in the consumption pattern of the household receiving remittances as compared to those who only get their income from domestic sources. Review of Related Literature There are several studies regarding the consumption patterns of household. One of which is the study made by Taylor and Mora (2006), they studied about the effect of migration in reshaping the expenditure of rural households in Mexico. The conclusion that they made is that remittances has positive effects on total expenditures and investment. They also found out that as the remittances of rural household increases, the proportion of the income on consumption decreases (Taylor Mora, 2006). Another one is the study of Rasyad A. Parinduri Shandre M. Thangavelu (2008), wherein they used the Indonesia Family Life Survey data to observe the effect of remittances to the consumption patterns of the Indonesian households. In their study, they used the matching and difference-in-difference matching estimators to observe the relationship. They found out that remittances do not improve the living standard of the households, nor do remittances have an effect on economic development. They used t he education and medical expenditure as indicators of economic development. The major findings that they have are that most of the Indonesian households used the remittances in terms of investing them into luxury goods such as house and jewelries (Parinduri Thangavelu, 2008). Using the same study, we intend to observe the consumption pattern of the households, based not only on the remittances but also to other sources of income. In addition to that, instead of looking at economic development, we intend to look at the consumption goods that households normally consume, and see if there are indeed changes in the consumption patterns of the selected households. Theoretical Framework Engelà ¢Ã¢â€š ¬Ã¢â€ž ¢s Law Methodology and Data In the methodology and data part, our main concern is to find ways to observe the consumption patterns of the Filipino households here in this country. In order to do that, we tried to find a dataset that will explain such relationship. Based from the available datasets here in the country, we would say that the Family Income and Expenditure Survey or the FIES best suits our study. The dataset enlists all the possible consumption goods that were being consumed by the households during a specific year. In addition to that, we can also determine the source of income of the different households that was made available in the dataset. By examining the relationship of consumption and income, we will be able to observe the behavioral aspect of the Filipino householdsà ¢Ã¢â€š ¬Ã¢â€ž ¢ consumption based from the income that they received. Due to the inaccessibility of the latest data, we settled for the 2003 edition. Based on this data, we will be able to observe the impact of the different sources of income to the kind of goods that the Filipino families consume, using an advanced econometric approach called the simultaneous equation model (SEM). After acquiring the right dataset for this study, we must next formulate the different structural equations to illustrate the consumption patterns. In this paper, we have formulated four equations, one of which is based from the Engelà ¢Ã¢â€š ¬Ã¢â€ž ¢s Law, which again, states that when an individualà ¢Ã¢â€š ¬Ã¢â€ž ¢s income increases, his/her percentage of consumption decreases (Engelà ¢Ã¢â€š ¬Ã¢â€ž ¢s Law, n.d.). As for the other three other equations which are mainly composed of different sources of income, mainly wages, domestic source, and foreign source, we have used other studies conducted by (SOURCE) ,to see what are the factors that affects or determine the different sources of income. After formulating the equations, we decided to use the log-log model for the estimation, simply because our study aims to observe the income elasticity of the different goods. With the use of the log-log model, we will be able to determine the elasticity of the different consumption goods, by just looking at their respective estimated coefficients. Another reason why we chose the log-log model is because of the limited information about the domestic and foreign source of income in the FIES data. There are several households in the data who either do not receive domestic or foreign source of income, or the data gatherers failed to obtain these data from the respective respondents. By using the log-log model, we will be able to exclude those unrecorded observations, so that the results will be not inconsistent and will not be affected by the people who do not receive income from either domestic or foreign source. After citing the reasons for the construction of the model, next, we will be observing three consumption goods, particularly the total food expenditures, the total non food expenditures, and the tobacco-alcohol consumption. Model 1: Food Consumption Equation 1: Equation 2: Equation 3: Equation 4: Where: food = total food expenditures Condo = domestic source of income Conab = foreign source of income Wage = wages or salaries of the household Wsag = wages or salaries from agricultural activities Wsnag = wages or salaries from non-agricultural activities S1021_age = household head age S1041_hgc = household head highest grade completed S1101_employed = total number of family employed with pay Lc10_conwr = contractual worker indicator In order to observe the consumption patterns of the Filipino household based from the different sources of income, we will be modifying the first equation of the model, by replacing one good to the other good, while maintaining the same structural forms. For example, in the initial first model, we have chosen food expenditure as our first consumption good. Later on, we will be observing other consumption goods such as non food expenditure, and alcoholic tobacco-alcohol consumption, and we will replace the food consumption with these other goods. This is because consumption goods are all affected by the income, and we have chosen the different income sources based from the availability of the FIES data, which was released on 2003. A-priori expectation Given the interrelationship of the equations, it seems like we have to solve the equations simultaneously to estimate for the unknown variables. Before we can use the simultaneous equation model (SEM) approach, there are several identification problems that we must solve in order to know whether SEM is an appropriate method or not. According to Gujarati and Porter (2009), the identification problem process consists of the following tests: a. order and rank condition, b. Hausman specification test, which is also known as the simultaneity test, and c. exogeneity test. Identification Problem Order and rank condition Before we proceed with the order and rank condition, we must first define the different variables that we will be using in order to test whether the equations are under-identified, exactly identified or over-identified. Legend: M à ¯Ã†â€™Ã‚  number of endogenous variables in the model m à ¯Ã†â€™Ã‚  number of endogenous variables in the equation K à ¯Ã†â€™Ã‚  number of exogenous/predetermined variables in the model k à ¯Ã†â€™Ã‚  number of exogenous/predetermined variables in the equation Order Condition The order condition is a necessary but not sufficient condition for identification (Gujarati and Porter, 2009). This test is used to see whether an equation is identified by comparing the number of excluded exogenous/predetermined variables in a given equation with the number of endogenous variables in the equation less one. There will be three instances where we can determine if the equation is identified or not. First, if K-k (number of excluded predetermined variables in the equation) In the first model, there are four endogenous variables namely lnfood, lnwages, lncondo, and lnconab (M=4). And there are also six exogenous variables in the equation which are the variables that were not named (K=6). With that, the order condition of the food consumption is illustrated below: Equation K-k m-1 Conclusion Lnfood 6 3 Over Lnwages 4 0 Over Lncondo 2 0 Over Lnconab 2 0 Over In the first case, all the equations are considered to be over-identified, simply because K-k > m-1. In the order condition, we have concluded that the model is identified. However, the order condition is not sufficiently enough to justify whether an equation is identified or not, that is why there is another condition that must be satisfied before we can proceed to the estimation process, which is the rank condition. Rank Condition The rank condition is a necessary and sufficient condition for identification. In order to satisfy the rank condition, à ¢Ã¢â€š ¬Ã…“there must be at least one nonzero determinant of order (M-1) (M-1) can be constructed from the coefficients of the variables excluded from that particular equation but included in the other equations of the modelà ¢Ã¢â€š ¬?(Gujarati and Porter, 2009). Ys Xs Eq. Food Wages condo conab 1 wssag wsnag hh_age hh_hgc employed conwr lnfood 1 0 0 0 0 0 0 lnwages 0 1 0 0 0 0 0 0 Lncondo 0 0 1 0 0 0 Lnconab 0 0 0 1 0 0 We simplify the variableà ¢Ã¢â€š ¬Ã¢â€ž ¢s notation, but ità ¢Ã¢â€š ¬Ã¢â€ž ¢s basically the same as the variables in the model, it only lacks the à ¢Ã¢â€š ¬Ã…“lnà ¢Ã¢â€š ¬? in some variables, and some variablesà ¢Ã¢â€š ¬Ã¢â€ž ¢ descriptions are shortened. We can observed that the (M-1) x (M-1), which in this case is 3 x 3 matrices, have at least one nonzero determinant, therefore the rank condition is satisfied. We can now proceed to the other identification test. Hausman specification test The Hausman specification test is to test whether the equations exhibits simultaneity problem or not. According to Gujarati and Porter (2009), if there is not simultaneity problem, then OLS is BLUE (best linear unbiased estimator). But if there is simultaneity problem, then OLS is not blue, because the estimated results will be bias and inconsistent. With that, we have to use the different estimation techniques of the SEM in order to regress the given equations. The Hausman specification test involves the following process: First, we regress an endogenous variable with respect to all of the exogenous/predetermined variables in the system, after which we obtain the value of the residual, in which it is the predictedThe second step is to regress the endogenous variable with respect to the other endogenous variables plus the predicted . If the is statistically significant, this means that we have all the evidence to reject the null hypothesis, which states that there is no simultaneity bias in the model. But if it is insignificant, we have no evidence to reject the null hypothesis, and if that happens, there is no simultaneity problem. The variable that exhibits no simultaneity bias should not be treated as an endogenous variable. (Gujarati and Porter, 2009) Dependent variable: lnwages P-values Independent variables: lncondo 0.370 lnconab 0.014 uhat 0.000 For the simultaneity test in the first model, we follow the steps in the Hausman specification test. After that, we observed the predicted uhat in this regression and we can see that the predicted uhat here is 0.000. This means that the null hypothesis is rejected, and there exist simultaneity bias in the first model, therefore we should use other estimation techniques other than OLS, to produce unbiased and consistent estimates. Exogeneity test After the simultaneity test, we must also test for the other exogenous/predetermined variables, to check whether these variables are truly exogenous or not. The process is similar to the Hausman specification test, but instead of regressing the endogenous variables, we regress each exogenous/predetermined variable with respect to the . If the is statistically significant, then we have to reject the null hypothesis that it is truly an exogenous variable. But if the p-value of the is 1.000, this means that we have no evidence to reject the null hypothesis, and we conclude that the corresponding variables are truly exogenous or truly predetermined variables. Exogenous variables à ¢Ã¢â€š ¬Ã¢â‚¬Å" 2nd equation Resulting p-values for uhat Lnwsag 1.000 lnwsnag 1.000 Exogenous variables à ¢Ã¢â€š ¬Ã¢â‚¬Å" 3nd equation Resulting p-values for uhat s1021_age 1.000 s1041_hgc 1.000 s1101_employed 1.000 lc10_conwr 1.000 Exogenous variables à ¢Ã¢â€š ¬Ã¢â‚¬Å" 4nd equation Resulting p-values for uhat s1021_age 1.000 s1041_hgc 1.000 s1101_employed 1.000 lc10_conwr 1.000 Based from the table given above, each exogenous variable is regressed against the predict uhat and looking at the respective p-values, which are all 1.000. This means that we have no evidence to reject that these variables are indeed truly exogenous variables in each of the equations. Model 2: Non Food Consumption Equation 1: Equation 2: Equation 3: Equation 4: Where: nonfood = total non food expenditure In model 2, we basically changed the total food expenditure with the total non food expenditure. Before we can regress the model, this model should also undergo series of identification problem process to see if whether the model is identified or not. We will also test if the nonfood expenditure model exhibits simultaneity bias and if all of its exogenous variables are truly exogenous. Order and Rank Condition Order Condition Equation K-k m-1 Conclusion Lnnonfood 6 3 Over Lnwages 4 0 Over Lncondo 2 0 Over Lnconab 2 0 Over Similar to the food consumption order condition, the non food consumption is also identified based on the order condition. All equations are concluded to be over-identified; therefore we can say that the model is identified. But again, we must use the rank condition to further validate if the equations are truly identified or not. Rank Condition Ys Xs Eq. nonfood wages condo conab 1 wssag wsnag hh_age hh_hgc employed conwr lnnonfood 1 0 0 0 0 0 0 lnwages 0 1 0 0 0 0 0 0 lncondo 0 0 1 0 0 0 lnconab 0 0 0 1 0 0 Based from the sub 33 matrices, we can say that there exists at least one nonzero determinant in the equation, therefore rank condition is satisfied. This means that the equations are identified. Hausman specification test Dependent variable: lnwages P-values Independent variables: lncondo 0.533 lnconab 0.011 uhat2 0.001 For the simultaneity test in model 2, we can see that uhat2 is statistically significant, meaning there exists a simultaneity bias in the model. Therefore we must use the SEM estimation techniques similar to model 1, to estimate the impact of income and consumption goods. Exogeneity test Exogenous variables à ¢Ã¢â€š ¬Ã¢â‚¬Å" 2nd equation Resulting p-values for uhat2 Lnwsag 1.000 lnwsnag 1.000 Exogenous variables à ¢Ã¢â€š ¬Ã¢â‚¬Å" 3nd equation Resulting p-values for uhat2 s1021_age 1.000 s1041_hgc 1.000 s1101_employed 1.000 lc10_conwr 1.000 Exogenous variables à ¢Ã¢â€š ¬Ã¢â‚¬Å" 4nd equation Resulting p-values for uhat2 s1021_age 1.000 s1041_hgc 1.000 s1101_employed 1.000 lc10_conwr 1.000 Similar to the food consumption model, the exogenous variables in the nonfood model are truly exogenous, since all the resulting p-values for uhat2, are all 1.000. Model 3: Tobacco-Alcohol Consumption Equation 1: Equation 2: Equation 3: Equation 4: Where: at = tobacco-alcohol consumption The same process in model 2 was made here in model 3, we now check for the identification problems for the tobacco-alcohol consumption Order and Rank Condition Order Condition Equation K-k m-1 Conclusion Lnat 6 3 Over Lnwages 4 0 Over Lncondo 2 0 Over Lnconab 2 0 Over Order condition is satisfied here in model 3, since all of the equations are concluded to be over-identification. We now proceed to the rank condition to check if the equations are ultimately identified. Rank Condition Ys Xs Eq. at wages condo conab 1 wssag wsnag hh_age hh_hgc employed conwr lnat 1 0 0 0 0 0 0 lnwages 0 1 0 0 0 0 0 0 lncondo 0 0 1 0 0 0 lnconab 0 0 0 1 0 0 Rank condition is satisfied because there is at least one nonzero determinant here in the sub 33 matrices. Hausman specification test Dependent variable: lnwages P-values Independent variables: lncondo 0.911 lnconab 0.063 uhat3 0.003 In model 3, there is no simultaneity problem because uhat3 is statistically significant. Therefore, we have all the evidence to reject the null hypothesis that there is no simultaneity bias in the equation. The same procedure as for food and nonfood model, we will be using the different estimation techniques to estimate these unknown variables. Estimation Techniques and Results Estimation Techniques After the identification problems of the simultaneous equation problem, we proceed to the estimation techniques. As discussed by Gujarati and Porter (2009), they provided three estimation techniques in order to solve for SEM, namely the ordinary least squares (OLS), indirect least squares (ILS), and the two-stage least squares (2SLS). The OLS is used for the recursive, triangular, or causal models (Gujarati and Porter, 2009). Meanwhile, the ILS focuses more on the reduced form of the simultaneous equations, wherein there exists only one endogenous variable in the reduced form equation and it is expressed in terms of all existing exogenous/predetermined variables in the model. It is estimated through the OLS approach, and this method best suits if the model is exactly identified (Gujarati and Porter, 2009). Lastly, the 2SLS approach, wherein the equations are estimated simultaneously. Unlike ILS, 2SLS can used to estimate exact and over-identified equations. (Gujarati and Porter, 2009 ) The three approaches discussed by Gujarati and Porter (2009) are all based from the single equation approach. If there are CLRM violations such as autocorrelation and heteroscedasticity in the models, we must use the system approach, particularly the three-stage least squares (3SLS), to correct these violations. The only drawback of the 3SLS method is that if any errors in one equation will affect the other equations. Ordinary Least Squares (OLS) Since all three models suffer from simultaneity bias, we will not use the OLS in this paper. This is because if we used the OLS in estimating the equation which there exist simultaneity bias, the results will be biased and inconsistent. Therefore, OLS is not a good estimator for the three models. Indirect Least Squares (ILS) Food consumption model reduced form: Where: | Nonfood model reduced form: Where: | Tobacco-Alcohol model reduced form: Where: | We will not estimate anymore the coefficient for the ILS, because our main goal is to observe the relationship of consumption goods with the different sources of income and not the other determinants of the different sources of income. The ILS results will not yield standard error for the structural coefficients; therefore it will be hard to obtain the values of the structural coefficients. In addition to that, all of our equations are over-identified, therefore ILS is an inappropriate method to estimate the coefficients. Two-stage least squares (2SLS) Consumption Goods Food (948 obs) Non Food (1078 obs) Tobacco-Alcohol (634 obs) 1st Equation Coefficients (P-value) Coefficients (P-value) Coefficients (P-value) constant 6.428484 (0.000) 1.401963 (0.070) 12.94298 (0.001) lnwages 0.2235283 (0.000) 0.2880426 (0.000) 0.7781965 (0.000) lncondo 0.0223739 (0.622) 0.2036453 (0.013) -1.47202 (0.000) lnconab 0.205797 (0.001) 0.5110999 (0.000) 0.6098058 (0.121) 2nd Eq. lnwages Coefficients (P-value) Coefficients (P-value) Coefficients (P-value) constant 2.122649 (0.000) 2.122649 (0.000) 1.884011 (0.000) lnwsag 0.3611279 (0.000) 0.3611279 (0.000) 0.42199 (0.000) lnwsnag 0.5175117 (0.000) 0.5175117 (0.000) 0.483135 (0.000) 3rd Eq. lncondo Coefficients (P-value) Coefficients (P-value) Coefficients (P-value) constant 7.75861 (0.000) 7.75861 (0.000) 7.887869 (0.000) s1021_age -0.0003422 (0.903) -0.0003422 (0.903) 0.0014345 (0.720) s1041_hgc 0.0346237 (0.000) 0.0346237 (0.000) 0.1302147 (0.000) s1101_employed -0.023387 (0.450) -0.023387 (0.450) -0.0601213 (0.111) lc10conwr 0.1583353 (0.345) 0.1583353 (0.345) 0.0871853 (0.710) 4th Eq. lnconab Coefficients (P-value) Coefficients (P-value) Coefficients (P-value) constant 10.39914 (0.000) 10.39914 (0.000) 9.947326 (0.000) s1021_age 0.004519 (0.169) 0.004519 (0.169) 0.0145833 (0.002) s1041_hgc 0.0210221 (0.000) 0.0210221 (0.000) 0.150857 (0.000) s1101_employed 0.0420871 (0.245) 0.0420871 (0.245) 0.0273189 (0.541) lc10conwr -0.6848394 (0.000) -0.6848394 (0.000) -0.7780885 (0.005) Since FIES is a cross sectional data, the model maybe exposed to the violations of multicollinearity and heteroscedasticity. As shown in the appendix1, under the CLRM violations, there exists no multicollinearity in the equations, but there exists heteroscedasticity three out of four equations in the model. The only way to correct for the heteroscedasticity problem is by estimating the simultaneous equations using the three-stage least squares method, which is considered to be full information approach. Three-stage least squares (3SLS) Consumption Goods Food (948 obs) Non Food (1078 obs) Tobacco-Alcohol (634 obs) 1st Equation Coefficients (P-value) Coefficients (P-value) Coefficients (P-value) constant 6.383871 (0.000) 0.7926094 (0.289) 18.63624 (0.000) lnwages 0.2224267 (0.000) 0.2831109 (0.000) 0.7374008 (0.000) lncondo 0.0245077 (0.582) 0.3151916 (0.000) -2.405262 (0.000) lnconab 0.2101956 (0.001) 0.4810778 (0.000) 0.9024638 (0.020) 2nd Eq. lnwages Coefficients (P-value) Coefficients (P-value) Coefficients (P-value) constant 2.142826 (0.000) 2.126479 (0.000) 1.895235 (0.000) lnwsag 0.3560053 (0.000) 0.3594587 (0.000) 0.419183 (0.000) lnwsnag 0.5203181 (0.000) 0.5187091 (0.000) 0.4846674 (0.000) 3rd Eq. lncondo Coefficients (P-value) Coefficients (P-value) Coefficients (P-value) constant 7.66644 (0.000) 7.420188 (0.000) 8.252266 (0.000) s1021_age 0.0000462 (0.987) -0.0005333 (0.840) 0.0042572 (0.224) s1041_hgc 0.0344578 (0.000) 0.0327889 (0.000) 0.0972984 (0.002) s1101_employed -0.0109756 (0.720) 0.030168 (0.302) -0.0811008 (0.009) lc10conwr 0.173369 (0.296) 0.234941 (0.151) -0.0362562 (0.860) 4th Eq. lnconab Coefficients (P-value) Coefficients (P-value) Coefficients (P-value) constant 9.635422 (0.000) 9.760654 (0.000) 9.899007 (0.000) s1021_age 0.0025551 (0.394) 0.0034051 (0.195) 0.0140427 (0.003) s1041_hgc 0.0212975 (0.000) 0.0171248 (0.000) 0.1589354 (0.000) s1101_employed 0.1534522 (0.000) 0.1464836 (0.000) 0.0291422 (0.510) lc10conwr -0.484862 (0.011) -0.5302148 (0.004) -0.761339 (0.006) By using the 3SLS, the models are now corrected and it is free from any CLRM violations. Therefore, the table shown above is already the final model of estimation, and we can now interpret the results equation per equation basis. Check for equality and unit elasticity As indicated in the appendices (last part), we also check if there lnwages and lnconab in the food consumption equation are indeed equal. We used the test command in STATA, to see if the two variables are equal, by looking at its p-value. The resulting p-value of the test is 0.8614, meaning we have no evidence to reject the null hypothesis that the two variablesà ¢Ã¢â€š ¬Ã¢â€ž ¢ coefficients are equal. We made the same process for the lnwages and lncondo in the nonfood consumption equation, and the resulting p-value of the test is 0.6846, which means that lnwages and lncondo are also equal in the estimation. Aside from the check for equality, we also check if the lnconabà ¢Ã¢â€š ¬Ã¢â€ž ¢s income elasticity to tobacco-alcohol consumption is equal to 1. The resulting p-value for the test is 0.8007, which means that the income elasticity of lnconab to tobacco-alcohol consumption is 1, meaning it is unit elastic. Results Model 1 à ¢Ã¢â€š ¬Ã¢â‚¬Å" Food Consumption In the first model, which is the total food expenditure model, the variable domestic source of income in the 1st equation is considered to be statistically insignificant. This means that it will be meaningless to interpret the results of that particular variable. As for wages and foreign source of income, we can see that the two coefficients are very similar, which means that for every one percent increase in wages and foreign source of income, food consumption increases by 0.22 and 0.21 percent respectively. The results are clearly consistent with Engelà ¢Ã¢â€š ¬Ã¢â€ž ¢s Law of food consumption that the proportion of food expenditure decrease as an individualà ¢Ã¢â€š ¬Ã¢â€ž ¢s income increases. For the 2nd equation, which is the wage equation, the result shows that the impact of non-agricultural activities is greater compared to agricultural activities. This is consistent with our a-priori expectation of one having a larger impact than the other. In reality, we can see that non-agricultural activities result to higher income due to its high value added products that it produces. The higher the value added the work is, the higher the changes are that wages or salaries received will be also higher. For the 3rd and 4th equation, which is considered to be similar except for the source of income where it comes from, the results show that only highest grade completed is considered to be statistically significant in the 3rd equation, while in the 4th equation, the household headà ¢Ã¢â€š ¬Ã¢â€ž ¢s age is the only one which is statistically insignificant. For the domestic source of income, we can observed that people who has a larger share of the wages or salaries in the company, have typically higher educational attainment compared to those who have lower educational attainment. The result of the 3rd equation maybe attributed to that factor. For the 4th equation, it is the same explanation for the highest grade completed by the household head as in the 3rd equation. While for the total family members employed with pay, it has a positive relationship, simply because if there are larger number of family members who are working and receiving salaries, the cumulative source of income wi ll be larger, compared to those families who have fewer number of family members working with pay. The last variable in the 4th equation, which is the dummy variable contract worker, we can see in the result that if an individual is a contract worker, generally, that individual will receive lower wages compared to those regular employees. This is because contractual workers are given limited period of time to work for certain companies, and companies hire contractual workers for short term uses. With that, companies usually pay lower amount of wages to these short term workers. Model 2 à ¢Ã¢â€š ¬Ã¢â‚¬Å" Non food consumption For the 2nd model, the nonfood consumption model, all the variables in the 1st equation are all statistically significant. The coefficients of wages and domestic source of income are similar, but there is a disparity between these two variables and the foreign source of income, which resulted to a higher coefficient. The higher coefficient means that the foreign source of income is more sensitive to nonfood consumption compared to the initial two variables à ¢Ã¢â€š ¬Ã¢â‚¬Å" wages and domestic income. We can see in the result that a ho Effect of Remittances on Household Consumption Patterns Effect of Remittances on Household Consumption Patterns Do remittances affect the consumption pattern of the Filipino households? Objectives The objective of this paper is to formulate structural models to illustrate the change in consumption pattern of the Filipino households. In this study, our aim is to use an advanced econometric approach to find out if there is indeed such change in the consumption pattern of the household receiving remittances as compared to those who only get their income from domestic sources. Review of Related Literature There are several studies regarding the consumption patterns of household. One of which is the study made by Taylor and Mora (2006), they studied about the effect of migration in reshaping the expenditure of rural households in Mexico. The conclusion that they made is that remittances has positive effects on total expenditures and investment. They also found out that as the remittances of rural household increases, the proportion of the income on consumption decreases (Taylor Mora, 2006). Another one is the study of Rasyad A. Parinduri Shandre M. Thangavelu (2008), wherein they used the Indonesia Family Life Survey data to observe the effect of remittances to the consumption patterns of the Indonesian households. In their study, they used the matching and difference-in-difference matching estimators to observe the relationship. They found out that remittances do not improve the living standard of the households, nor do remittances have an effect on economic development. They used t he education and medical expenditure as indicators of economic development. The major findings that they have are that most of the Indonesian households used the remittances in terms of investing them into luxury goods such as house and jewelries (Parinduri Thangavelu, 2008). Using the same study, we intend to observe the consumption pattern of the households, based not only on the remittances but also to other sources of income. In addition to that, instead of looking at economic development, we intend to look at the consumption goods that households normally consume, and see if there are indeed changes in the consumption patterns of the selected households. Theoretical Framework Engelà ¢Ã¢â€š ¬Ã¢â€ž ¢s Law Methodology and Data In the methodology and data part, our main concern is to find ways to observe the consumption patterns of the Filipino households here in this country. In order to do that, we tried to find a dataset that will explain such relationship. Based from the available datasets here in the country, we would say that the Family Income and Expenditure Survey or the FIES best suits our study. The dataset enlists all the possible consumption goods that were being consumed by the households during a specific year. In addition to that, we can also determine the source of income of the different households that was made available in the dataset. By examining the relationship of consumption and income, we will be able to observe the behavioral aspect of the Filipino householdsà ¢Ã¢â€š ¬Ã¢â€ž ¢ consumption based from the income that they received. Due to the inaccessibility of the latest data, we settled for the 2003 edition. Based on this data, we will be able to observe the impact of the different sources of income to the kind of goods that the Filipino families consume, using an advanced econometric approach called the simultaneous equation model (SEM). After acquiring the right dataset for this study, we must next formulate the different structural equations to illustrate the consumption patterns. In this paper, we have formulated four equations, one of which is based from the Engelà ¢Ã¢â€š ¬Ã¢â€ž ¢s Law, which again, states that when an individualà ¢Ã¢â€š ¬Ã¢â€ž ¢s income increases, his/her percentage of consumption decreases (Engelà ¢Ã¢â€š ¬Ã¢â€ž ¢s Law, n.d.). As for the other three other equations which are mainly composed of different sources of income, mainly wages, domestic source, and foreign source, we have used other studies conducted by (SOURCE) ,to see what are the factors that affects or determine the different sources of income. After formulating the equations, we decided to use the log-log model for the estimation, simply because our study aims to observe the income elasticity of the different goods. With the use of the log-log model, we will be able to determine the elasticity of the different consumption goods, by just looking at their respective estimated coefficients. Another reason why we chose the log-log model is because of the limited information about the domestic and foreign source of income in the FIES data. There are several households in the data who either do not receive domestic or foreign source of income, or the data gatherers failed to obtain these data from the respective respondents. By using the log-log model, we will be able to exclude those unrecorded observations, so that the results will be not inconsistent and will not be affected by the people who do not receive income from either domestic or foreign source. After citing the reasons for the construction of the model, next, we will be observing three consumption goods, particularly the total food expenditures, the total non food expenditures, and the tobacco-alcohol consumption. Model 1: Food Consumption Equation 1: Equation 2: Equation 3: Equation 4: Where: food = total food expenditures Condo = domestic source of income Conab = foreign source of income Wage = wages or salaries of the household Wsag = wages or salaries from agricultural activities Wsnag = wages or salaries from non-agricultural activities S1021_age = household head age S1041_hgc = household head highest grade completed S1101_employed = total number of family employed with pay Lc10_conwr = contractual worker indicator In order to observe the consumption patterns of the Filipino household based from the different sources of income, we will be modifying the first equation of the model, by replacing one good to the other good, while maintaining the same structural forms. For example, in the initial first model, we have chosen food expenditure as our first consumption good. Later on, we will be observing other consumption goods such as non food expenditure, and alcoholic tobacco-alcohol consumption, and we will replace the food consumption with these other goods. This is because consumption goods are all affected by the income, and we have chosen the different income sources based from the availability of the FIES data, which was released on 2003. A-priori expectation Given the interrelationship of the equations, it seems like we have to solve the equations simultaneously to estimate for the unknown variables. Before we can use the simultaneous equation model (SEM) approach, there are several identification problems that we must solve in order to know whether SEM is an appropriate method or not. According to Gujarati and Porter (2009), the identification problem process consists of the following tests: a. order and rank condition, b. Hausman specification test, which is also known as the simultaneity test, and c. exogeneity test. Identification Problem Order and rank condition Before we proceed with the order and rank condition, we must first define the different variables that we will be using in order to test whether the equations are under-identified, exactly identified or over-identified. Legend: M à ¯Ã†â€™Ã‚  number of endogenous variables in the model m à ¯Ã†â€™Ã‚  number of endogenous variables in the equation K à ¯Ã†â€™Ã‚  number of exogenous/predetermined variables in the model k à ¯Ã†â€™Ã‚  number of exogenous/predetermined variables in the equation Order Condition The order condition is a necessary but not sufficient condition for identification (Gujarati and Porter, 2009). This test is used to see whether an equation is identified by comparing the number of excluded exogenous/predetermined variables in a given equation with the number of endogenous variables in the equation less one. There will be three instances where we can determine if the equation is identified or not. First, if K-k (number of excluded predetermined variables in the equation) In the first model, there are four endogenous variables namely lnfood, lnwages, lncondo, and lnconab (M=4). And there are also six exogenous variables in the equation which are the variables that were not named (K=6). With that, the order condition of the food consumption is illustrated below: Equation K-k m-1 Conclusion Lnfood 6 3 Over Lnwages 4 0 Over Lncondo 2 0 Over Lnconab 2 0 Over In the first case, all the equations are considered to be over-identified, simply because K-k > m-1. In the order condition, we have concluded that the model is identified. However, the order condition is not sufficiently enough to justify whether an equation is identified or not, that is why there is another condition that must be satisfied before we can proceed to the estimation process, which is the rank condition. Rank Condition The rank condition is a necessary and sufficient condition for identification. In order to satisfy the rank condition, à ¢Ã¢â€š ¬Ã…“there must be at least one nonzero determinant of order (M-1) (M-1) can be constructed from the coefficients of the variables excluded from that particular equation but included in the other equations of the modelà ¢Ã¢â€š ¬?(Gujarati and Porter, 2009). Ys Xs Eq. Food Wages condo conab 1 wssag wsnag hh_age hh_hgc employed conwr lnfood 1 0 0 0 0 0 0 lnwages 0 1 0 0 0 0 0 0 Lncondo 0 0 1 0 0 0 Lnconab 0 0 0 1 0 0 We simplify the variableà ¢Ã¢â€š ¬Ã¢â€ž ¢s notation, but ità ¢Ã¢â€š ¬Ã¢â€ž ¢s basically the same as the variables in the model, it only lacks the à ¢Ã¢â€š ¬Ã…“lnà ¢Ã¢â€š ¬? in some variables, and some variablesà ¢Ã¢â€š ¬Ã¢â€ž ¢ descriptions are shortened. We can observed that the (M-1) x (M-1), which in this case is 3 x 3 matrices, have at least one nonzero determinant, therefore the rank condition is satisfied. We can now proceed to the other identification test. Hausman specification test The Hausman specification test is to test whether the equations exhibits simultaneity problem or not. According to Gujarati and Porter (2009), if there is not simultaneity problem, then OLS is BLUE (best linear unbiased estimator). But if there is simultaneity problem, then OLS is not blue, because the estimated results will be bias and inconsistent. With that, we have to use the different estimation techniques of the SEM in order to regress the given equations. The Hausman specification test involves the following process: First, we regress an endogenous variable with respect to all of the exogenous/predetermined variables in the system, after which we obtain the value of the residual, in which it is the predictedThe second step is to regress the endogenous variable with respect to the other endogenous variables plus the predicted . If the is statistically significant, this means that we have all the evidence to reject the null hypothesis, which states that there is no simultaneity bias in the model. But if it is insignificant, we have no evidence to reject the null hypothesis, and if that happens, there is no simultaneity problem. The variable that exhibits no simultaneity bias should not be treated as an endogenous variable. (Gujarati and Porter, 2009) Dependent variable: lnwages P-values Independent variables: lncondo 0.370 lnconab 0.014 uhat 0.000 For the simultaneity test in the first model, we follow the steps in the Hausman specification test. After that, we observed the predicted uhat in this regression and we can see that the predicted uhat here is 0.000. This means that the null hypothesis is rejected, and there exist simultaneity bias in the first model, therefore we should use other estimation techniques other than OLS, to produce unbiased and consistent estimates. Exogeneity test After the simultaneity test, we must also test for the other exogenous/predetermined variables, to check whether these variables are truly exogenous or not. The process is similar to the Hausman specification test, but instead of regressing the endogenous variables, we regress each exogenous/predetermined variable with respect to the . If the is statistically significant, then we have to reject the null hypothesis that it is truly an exogenous variable. But if the p-value of the is 1.000, this means that we have no evidence to reject the null hypothesis, and we conclude that the corresponding variables are truly exogenous or truly predetermined variables. Exogenous variables à ¢Ã¢â€š ¬Ã¢â‚¬Å" 2nd equation Resulting p-values for uhat Lnwsag 1.000 lnwsnag 1.000 Exogenous variables à ¢Ã¢â€š ¬Ã¢â‚¬Å" 3nd equation Resulting p-values for uhat s1021_age 1.000 s1041_hgc 1.000 s1101_employed 1.000 lc10_conwr 1.000 Exogenous variables à ¢Ã¢â€š ¬Ã¢â‚¬Å" 4nd equation Resulting p-values for uhat s1021_age 1.000 s1041_hgc 1.000 s1101_employed 1.000 lc10_conwr 1.000 Based from the table given above, each exogenous variable is regressed against the predict uhat and looking at the respective p-values, which are all 1.000. This means that we have no evidence to reject that these variables are indeed truly exogenous variables in each of the equations. Model 2: Non Food Consumption Equation 1: Equation 2: Equation 3: Equation 4: Where: nonfood = total non food expenditure In model 2, we basically changed the total food expenditure with the total non food expenditure. Before we can regress the model, this model should also undergo series of identification problem process to see if whether the model is identified or not. We will also test if the nonfood expenditure model exhibits simultaneity bias and if all of its exogenous variables are truly exogenous. Order and Rank Condition Order Condition Equation K-k m-1 Conclusion Lnnonfood 6 3 Over Lnwages 4 0 Over Lncondo 2 0 Over Lnconab 2 0 Over Similar to the food consumption order condition, the non food consumption is also identified based on the order condition. All equations are concluded to be over-identified; therefore we can say that the model is identified. But again, we must use the rank condition to further validate if the equations are truly identified or not. Rank Condition Ys Xs Eq. nonfood wages condo conab 1 wssag wsnag hh_age hh_hgc employed conwr lnnonfood 1 0 0 0 0 0 0 lnwages 0 1 0 0 0 0 0 0 lncondo 0 0 1 0 0 0 lnconab 0 0 0 1 0 0 Based from the sub 33 matrices, we can say that there exists at least one nonzero determinant in the equation, therefore rank condition is satisfied. This means that the equations are identified. Hausman specification test Dependent variable: lnwages P-values Independent variables: lncondo 0.533 lnconab 0.011 uhat2 0.001 For the simultaneity test in model 2, we can see that uhat2 is statistically significant, meaning there exists a simultaneity bias in the model. Therefore we must use the SEM estimation techniques similar to model 1, to estimate the impact of income and consumption goods. Exogeneity test Exogenous variables à ¢Ã¢â€š ¬Ã¢â‚¬Å" 2nd equation Resulting p-values for uhat2 Lnwsag 1.000 lnwsnag 1.000 Exogenous variables à ¢Ã¢â€š ¬Ã¢â‚¬Å" 3nd equation Resulting p-values for uhat2 s1021_age 1.000 s1041_hgc 1.000 s1101_employed 1.000 lc10_conwr 1.000 Exogenous variables à ¢Ã¢â€š ¬Ã¢â‚¬Å" 4nd equation Resulting p-values for uhat2 s1021_age 1.000 s1041_hgc 1.000 s1101_employed 1.000 lc10_conwr 1.000 Similar to the food consumption model, the exogenous variables in the nonfood model are truly exogenous, since all the resulting p-values for uhat2, are all 1.000. Model 3: Tobacco-Alcohol Consumption Equation 1: Equation 2: Equation 3: Equation 4: Where: at = tobacco-alcohol consumption The same process in model 2 was made here in model 3, we now check for the identification problems for the tobacco-alcohol consumption Order and Rank Condition Order Condition Equation K-k m-1 Conclusion Lnat 6 3 Over Lnwages 4 0 Over Lncondo 2 0 Over Lnconab 2 0 Over Order condition is satisfied here in model 3, since all of the equations are concluded to be over-identification. We now proceed to the rank condition to check if the equations are ultimately identified. Rank Condition Ys Xs Eq. at wages condo conab 1 wssag wsnag hh_age hh_hgc employed conwr lnat 1 0 0 0 0 0 0 lnwages 0 1 0 0 0 0 0 0 lncondo 0 0 1 0 0 0 lnconab 0 0 0 1 0 0 Rank condition is satisfied because there is at least one nonzero determinant here in the sub 33 matrices. Hausman specification test Dependent variable: lnwages P-values Independent variables: lncondo 0.911 lnconab 0.063 uhat3 0.003 In model 3, there is no simultaneity problem because uhat3 is statistically significant. Therefore, we have all the evidence to reject the null hypothesis that there is no simultaneity bias in the equation. The same procedure as for food and nonfood model, we will be using the different estimation techniques to estimate these unknown variables. Estimation Techniques and Results Estimation Techniques After the identification problems of the simultaneous equation problem, we proceed to the estimation techniques. As discussed by Gujarati and Porter (2009), they provided three estimation techniques in order to solve for SEM, namely the ordinary least squares (OLS), indirect least squares (ILS), and the two-stage least squares (2SLS). The OLS is used for the recursive, triangular, or causal models (Gujarati and Porter, 2009). Meanwhile, the ILS focuses more on the reduced form of the simultaneous equations, wherein there exists only one endogenous variable in the reduced form equation and it is expressed in terms of all existing exogenous/predetermined variables in the model. It is estimated through the OLS approach, and this method best suits if the model is exactly identified (Gujarati and Porter, 2009). Lastly, the 2SLS approach, wherein the equations are estimated simultaneously. Unlike ILS, 2SLS can used to estimate exact and over-identified equations. (Gujarati and Porter, 2009 ) The three approaches discussed by Gujarati and Porter (2009) are all based from the single equation approach. If there are CLRM violations such as autocorrelation and heteroscedasticity in the models, we must use the system approach, particularly the three-stage least squares (3SLS), to correct these violations. The only drawback of the 3SLS method is that if any errors in one equation will affect the other equations. Ordinary Least Squares (OLS) Since all three models suffer from simultaneity bias, we will not use the OLS in this paper. This is because if we used the OLS in estimating the equation which there exist simultaneity bias, the results will be biased and inconsistent. Therefore, OLS is not a good estimator for the three models. Indirect Least Squares (ILS) Food consumption model reduced form: Where: | Nonfood model reduced form: Where: | Tobacco-Alcohol model reduced form: Where: | We will not estimate anymore the coefficient for the ILS, because our main goal is to observe the relationship of consumption goods with the different sources of income and not the other determinants of the different sources of income. The ILS results will not yield standard error for the structural coefficients; therefore it will be hard to obtain the values of the structural coefficients. In addition to that, all of our equations are over-identified, therefore ILS is an inappropriate method to estimate the coefficients. Two-stage least squares (2SLS) Consumption Goods Food (948 obs) Non Food (1078 obs) Tobacco-Alcohol (634 obs) 1st Equation Coefficients (P-value) Coefficients (P-value) Coefficients (P-value) constant 6.428484 (0.000) 1.401963 (0.070) 12.94298 (0.001) lnwages 0.2235283 (0.000) 0.2880426 (0.000) 0.7781965 (0.000) lncondo 0.0223739 (0.622) 0.2036453 (0.013) -1.47202 (0.000) lnconab 0.205797 (0.001) 0.5110999 (0.000) 0.6098058 (0.121) 2nd Eq. lnwages Coefficients (P-value) Coefficients (P-value) Coefficients (P-value) constant 2.122649 (0.000) 2.122649 (0.000) 1.884011 (0.000) lnwsag 0.3611279 (0.000) 0.3611279 (0.000) 0.42199 (0.000) lnwsnag 0.5175117 (0.000) 0.5175117 (0.000) 0.483135 (0.000) 3rd Eq. lncondo Coefficients (P-value) Coefficients (P-value) Coefficients (P-value) constant 7.75861 (0.000) 7.75861 (0.000) 7.887869 (0.000) s1021_age -0.0003422 (0.903) -0.0003422 (0.903) 0.0014345 (0.720) s1041_hgc 0.0346237 (0.000) 0.0346237 (0.000) 0.1302147 (0.000) s1101_employed -0.023387 (0.450) -0.023387 (0.450) -0.0601213 (0.111) lc10conwr 0.1583353 (0.345) 0.1583353 (0.345) 0.0871853 (0.710) 4th Eq. lnconab Coefficients (P-value) Coefficients (P-value) Coefficients (P-value) constant 10.39914 (0.000) 10.39914 (0.000) 9.947326 (0.000) s1021_age 0.004519 (0.169) 0.004519 (0.169) 0.0145833 (0.002) s1041_hgc 0.0210221 (0.000) 0.0210221 (0.000) 0.150857 (0.000) s1101_employed 0.0420871 (0.245) 0.0420871 (0.245) 0.0273189 (0.541) lc10conwr -0.6848394 (0.000) -0.6848394 (0.000) -0.7780885 (0.005) Since FIES is a cross sectional data, the model maybe exposed to the violations of multicollinearity and heteroscedasticity. As shown in the appendix1, under the CLRM violations, there exists no multicollinearity in the equations, but there exists heteroscedasticity three out of four equations in the model. The only way to correct for the heteroscedasticity problem is by estimating the simultaneous equations using the three-stage least squares method, which is considered to be full information approach. Three-stage least squares (3SLS) Consumption Goods Food (948 obs) Non Food (1078 obs) Tobacco-Alcohol (634 obs) 1st Equation Coefficients (P-value) Coefficients (P-value) Coefficients (P-value) constant 6.383871 (0.000) 0.7926094 (0.289) 18.63624 (0.000) lnwages 0.2224267 (0.000) 0.2831109 (0.000) 0.7374008 (0.000) lncondo 0.0245077 (0.582) 0.3151916 (0.000) -2.405262 (0.000) lnconab 0.2101956 (0.001) 0.4810778 (0.000) 0.9024638 (0.020) 2nd Eq. lnwages Coefficients (P-value) Coefficients (P-value) Coefficients (P-value) constant 2.142826 (0.000) 2.126479 (0.000) 1.895235 (0.000) lnwsag 0.3560053 (0.000) 0.3594587 (0.000) 0.419183 (0.000) lnwsnag 0.5203181 (0.000) 0.5187091 (0.000) 0.4846674 (0.000) 3rd Eq. lncondo Coefficients (P-value) Coefficients (P-value) Coefficients (P-value) constant 7.66644 (0.000) 7.420188 (0.000) 8.252266 (0.000) s1021_age 0.0000462 (0.987) -0.0005333 (0.840) 0.0042572 (0.224) s1041_hgc 0.0344578 (0.000) 0.0327889 (0.000) 0.0972984 (0.002) s1101_employed -0.0109756 (0.720) 0.030168 (0.302) -0.0811008 (0.009) lc10conwr 0.173369 (0.296) 0.234941 (0.151) -0.0362562 (0.860) 4th Eq. lnconab Coefficients (P-value) Coefficients (P-value) Coefficients (P-value) constant 9.635422 (0.000) 9.760654 (0.000) 9.899007 (0.000) s1021_age 0.0025551 (0.394) 0.0034051 (0.195) 0.0140427 (0.003) s1041_hgc 0.0212975 (0.000) 0.0171248 (0.000) 0.1589354 (0.000) s1101_employed 0.1534522 (0.000) 0.1464836 (0.000) 0.0291422 (0.510) lc10conwr -0.484862 (0.011) -0.5302148 (0.004) -0.761339 (0.006) By using the 3SLS, the models are now corrected and it is free from any CLRM violations. Therefore, the table shown above is already the final model of estimation, and we can now interpret the results equation per equation basis. Check for equality and unit elasticity As indicated in the appendices (last part), we also check if there lnwages and lnconab in the food consumption equation are indeed equal. We used the test command in STATA, to see if the two variables are equal, by looking at its p-value. The resulting p-value of the test is 0.8614, meaning we have no evidence to reject the null hypothesis that the two variablesà ¢Ã¢â€š ¬Ã¢â€ž ¢ coefficients are equal. We made the same process for the lnwages and lncondo in the nonfood consumption equation, and the resulting p-value of the test is 0.6846, which means that lnwages and lncondo are also equal in the estimation. Aside from the check for equality, we also check if the lnconabà ¢Ã¢â€š ¬Ã¢â€ž ¢s income elasticity to tobacco-alcohol consumption is equal to 1. The resulting p-value for the test is 0.8007, which means that the income elasticity of lnconab to tobacco-alcohol consumption is 1, meaning it is unit elastic. Results Model 1 à ¢Ã¢â€š ¬Ã¢â‚¬Å" Food Consumption In the first model, which is the total food expenditure model, the variable domestic source of income in the 1st equation is considered to be statistically insignificant. This means that it will be meaningless to interpret the results of that particular variable. As for wages and foreign source of income, we can see that the two coefficients are very similar, which means that for every one percent increase in wages and foreign source of income, food consumption increases by 0.22 and 0.21 percent respectively. The results are clearly consistent with Engelà ¢Ã¢â€š ¬Ã¢â€ž ¢s Law of food consumption that the proportion of food expenditure decrease as an individualà ¢Ã¢â€š ¬Ã¢â€ž ¢s income increases. For the 2nd equation, which is the wage equation, the result shows that the impact of non-agricultural activities is greater compared to agricultural activities. This is consistent with our a-priori expectation of one having a larger impact than the other. In reality, we can see that non-agricultural activities result to higher income due to its high value added products that it produces. The higher the value added the work is, the higher the changes are that wages or salaries received will be also higher. For the 3rd and 4th equation, which is considered to be similar except for the source of income where it comes from, the results show that only highest grade completed is considered to be statistically significant in the 3rd equation, while in the 4th equation, the household headà ¢Ã¢â€š ¬Ã¢â€ž ¢s age is the only one which is statistically insignificant. For the domestic source of income, we can observed that people who has a larger share of the wages or salaries in the company, have typically higher educational attainment compared to those who have lower educational attainment. The result of the 3rd equation maybe attributed to that factor. For the 4th equation, it is the same explanation for the highest grade completed by the household head as in the 3rd equation. While for the total family members employed with pay, it has a positive relationship, simply because if there are larger number of family members who are working and receiving salaries, the cumulative source of income wi ll be larger, compared to those families who have fewer number of family members working with pay. The last variable in the 4th equation, which is the dummy variable contract worker, we can see in the result that if an individual is a contract worker, generally, that individual will receive lower wages compared to those regular employees. This is because contractual workers are given limited period of time to work for certain companies, and companies hire contractual workers for short term uses. With that, companies usually pay lower amount of wages to these short term workers. Model 2 à ¢Ã¢â€š ¬Ã¢â‚¬Å" Non food consumption For the 2nd model, the nonfood consumption model, all the variables in the 1st equation are all statistically significant. The coefficients of wages and domestic source of income are similar, but there is a disparity between these two variables and the foreign source of income, which resulted to a higher coefficient. The higher coefficient means that the foreign source of income is more sensitive to nonfood consumption compared to the initial two variables à ¢Ã¢â€š ¬Ã¢â‚¬Å" wages and domestic income. We can see in the result that a ho

Movies Serendipity and An Affair to Remember :: Serendipity Affair Movie Film Essays

Movies Serendipity and An Affair to Remember Can once in a lifetime happen twice? Can two people get a second chance at love? While reality more than likely suggests no, some movies would suggest otherwise. The films An Affair to Remember and Serendipity are only two examples of how society depicts romance as an exaggerated fabrication of reality only to have a negative effect on its viewers. Both films share the storyline of two lovers who separate, only hoping that fate will bring them back together As the film Serendipity begins, Sara Thomas and Jonathon Trager meet each other for the first time at Bloomingdale’s. Conversation sparked between the two when both reached for the same pair of gloves. Enjoying themselves at Bloomingdales, Sara and Jonathon decide to further their discussion at a nearby restaurant called Serendipity. Here, Jonathon realizes that he wants to see Sara again and politely asks for her phone number. Instead of just handing her number over, Sara writes in down on the inside cover of book, which she then tells him that she will sell the next day at a used bookstore. She continues to explain to Jonathon that if they are truly meant to see each other again, the book will find him. Jonathon then opens his wallet to take out a dollar bill. He writes his phone number on it and gives it to Sara, who spends it immediately. Using the same logic as before, she tells him that the dollar bill will find it’s way to her. As the years pass, the two both go on living their lives. But, Sara and Jonathon can’t seem to shake the feeling of each other. Every time Sara has a dollar bill, she always looks for a phone number and Jonathon can’t count all the used bookstores he’s been to. They both eventually meet someone new and become engaged. They wonder if these people they plan on marrying are their true soul mates. The night of Jonathon’s wedding rehearsal, he fiancà © gives him a present. Opening it slowly, he comes to realize it’s the title of the book Sara had once written her phone number in. He opens the front cover and he reads Sara’s name and number. Meanwhile, Sara is on an airplane returning home from visiting a friend. Pulling out her wallet, she discovers that she doesn’t have her wallet, but she has mistakenly taken her friend’s. Movies Serendipity and An Affair to Remember :: Serendipity Affair Movie Film Essays Movies Serendipity and An Affair to Remember Can once in a lifetime happen twice? Can two people get a second chance at love? While reality more than likely suggests no, some movies would suggest otherwise. The films An Affair to Remember and Serendipity are only two examples of how society depicts romance as an exaggerated fabrication of reality only to have a negative effect on its viewers. Both films share the storyline of two lovers who separate, only hoping that fate will bring them back together As the film Serendipity begins, Sara Thomas and Jonathon Trager meet each other for the first time at Bloomingdale’s. Conversation sparked between the two when both reached for the same pair of gloves. Enjoying themselves at Bloomingdales, Sara and Jonathon decide to further their discussion at a nearby restaurant called Serendipity. Here, Jonathon realizes that he wants to see Sara again and politely asks for her phone number. Instead of just handing her number over, Sara writes in down on the inside cover of book, which she then tells him that she will sell the next day at a used bookstore. She continues to explain to Jonathon that if they are truly meant to see each other again, the book will find him. Jonathon then opens his wallet to take out a dollar bill. He writes his phone number on it and gives it to Sara, who spends it immediately. Using the same logic as before, she tells him that the dollar bill will find it’s way to her. As the years pass, the two both go on living their lives. But, Sara and Jonathon can’t seem to shake the feeling of each other. Every time Sara has a dollar bill, she always looks for a phone number and Jonathon can’t count all the used bookstores he’s been to. They both eventually meet someone new and become engaged. They wonder if these people they plan on marrying are their true soul mates. The night of Jonathon’s wedding rehearsal, he fiancà © gives him a present. Opening it slowly, he comes to realize it’s the title of the book Sara had once written her phone number in. He opens the front cover and he reads Sara’s name and number. Meanwhile, Sara is on an airplane returning home from visiting a friend. Pulling out her wallet, she discovers that she doesn’t have her wallet, but she has mistakenly taken her friend’s.

Ron Howard :: essays research papers

Ronald William Howard was born March 1st, 1954 in Duncan, Oklahoma. He is the older of two brothers. His parents, Rance Howard his father was an actor, director and writer, his mother Jean Howard was an actress, in 1959 his family relocated to Hollywood. Young Ron quickly joined the family business and his first television role was on an episode of "Playhouse 90" and was followed by an appearance on "The Red Skelton Show." He also was in four episodes of "Denis the Menace" and five shows of "The Many Loves of Dobie Gillis." (Encarta) Ron has the face that refused to age. No matter how much of his hair he looses, or how much of a beard he grows, he continues to have a boyish charm. For some viewers he is always remembered as Opie Taylor and to others as Richie Cunningham, while the more populated group of the confused he is know as Opie Cunningham. (sitcomsonline) The television producer Sheldon Leonard, who had seen Howard’s performance in Barnaby and Mr. O’Mally, cast the actor in the "Andy Griffith Show" which began its eight years on CBS on October 3, 1960. The gentle and subtle comedy of the show was set in the sleepy town of Mayberry, North Carolina, and was centered on the daily lives of sheriff Andy Taylor (Griffith), his young son, Opie (Howard), Aunt Bee (Frances Bavier), who was the live in housekeeper and Opei’s surrogate mother, and Barney Fife (Don Knotts), Andy’s deputy. The scenes between Andy and Opie were sensitively written by Ron’s father with similarities of their relationship, some of Opeis lines were also written by his father. Howard’s parents intervened in certain ways in his life since he was a child star like making sure certain aspects of contracts said didn’t say that he had to do promotional tours. When he was not working he was enrolled in public schools so he could interact with other kids his age. "In school I was a novelty at first," Howard told Edwin Miller. "People got very jazzed up about the idea of having a kid actor in class. That would blow over in a couple of weeks, and then I was able to blend right in." Howard later made the basketball team at Burroughs High School in Burbank; Howard then had to turn down acting assignments so he wouldn’t miss any basketball games.

Medicine in the Fight against HIV/AIDS and Cancer :: Medical Treatment Chinese Papers

Medicine in the Fight against HIV/AIDS and Cancer Conventional (allopathic) medicine has been the mainstream Western approach to medicine ever since the early twentieth century. Previous to the widespread popularization of the allopathic tradition, other more holistic traditions of medicine were accepted and practiced without bias. The founding of the American Medical Association (AMA) brought with it a swift turnabout for other traditions and placed the monopoly of the industry solely in the hands of allopathic physicians. However many of the procedures and techniques for dealing with illness in conventional medicine are invasive and involve the introduction of severe and even toxic agents and many people are now expressing a desire to return to more natural means of fighting disease. The use of alternative medicine is becoming increasingly popular in the Western world, although patients are hesitant to inform their allopathic physicians of this use. The prevalence of HIV/AIDS and Cancer cases is growing in leaps daily and these diseases even represent the leading causes of mortality in some countries. Conventional medicine is undoubtedly not always able to successfully treat many of these cases but it has been suggested that a combination of allopathic and alternative therapy would increase success rates by providing the optimal treatment of illness, as in the treatment of HIV/AIDS and Cancer. Western culture should endeavor to explore alternative practices instead of brushing aside what it does not understand. There are many different forms of alternative medicine, some of which are centuries old. The term 'alternative medicine' covers the broad category of unconventional forms of medicine, many of which are not accepted by the allopathic tradition due to their inability to be evaluated under the scientific method and their consequent lack of empiricality, both of which have strong bases in the Western tradition. The systems that fall under alternative medicine are Chinese Medicine, Ayurveda, Naturopathic Medicine, Homeopathy, Osteopathic Medicine, Chiropractic, Massage Therapy and Bodywork, and Mind/Body Medicine. Five of these treatments will be discussed in their general approaches to illness as a demonstration of alternative models of medicine. Chinese Medicine is an ancient form of alternative medicine, dating back over 3000 years. The key principle of this tradition is the belief in an unseen entity called chi, which symbolizes the vital life force energy inherent in all things. Chi flows through the human body in pathways known as meridians, which enable the passage of this energizing force through all the organs of the body.

Community Health Nursing Essay

Optional: As the school nurse role evolves, there are increasingly more health concerns for the school nurse. Does the locale make a difference in the problems, or are health problems in children and adolescents universal? In some inner-city areas, violence is a prevalent issue. What do you think are the biggest problems in your areas? The role of the school nurse has definitely evolved since I was in school. I remember the school nurse in elementary school was very kind in her starched white uniform and when you went to the â€Å"clinic† you were told to lay down on a cot and put a cool washcloth on your forehead. According to Nies & McEwan, many of today’s health challenges are different from those of the past and include behaviors and risks linked to the leading causes of death such as heart disease, injuries, and cancer (p. 580). There is an increase among young people to participate in unhealthy behavior such as smoking, drinking, drugs, and poor nutrition, decrease physical activity, increase sexual behavior, violence, suicide, that will put them at a risk for health problems (Nies & McEwan, 2015) In 2013, the population of Chesapeake, Virginia is 230,571 (United Stated Census Bureau) Chesapeake Public School Nurses in 2011-2012 treated 681,526 students in their clinic; treated 117,058 ill stude nts; treated 98,041 students that needed first aid and injured themselves; performed 62, 089 nursing procedures; counseled 175, 158 students and parents; and administered 128, 869 medications (Chesapeake Public Schools, 2012). WOW, that is a lot of  patients! This week’s lessons discusses the evolving role of the school nurse not only attending the students’ needs but involvement in â€Å"policy-making activities at both the local and state levels (CCN, 2015) The question proposed in this week’s lesson regarding some of the roles for the community health nurses is also applicable to the school nurse. The school nurse is the clinician, case manager, advocate, educator, researcher, administrator, change agent, case finder, coordinator and consultant in order to meet the complex needs of students. According to Nies & McEwen, many of today’s health challenges are different from those of the past and include behaviors and risks linked to the leading causes of death such as heart disease, injuries, and cancer. In the suburb that I live in there has been no violence reported by students in the school system that my daughter is a fifth grade teacher. I think the locale of the school system can increase potential risk for violence. In the school system that my daughter is a teacher she says that they deal more with behavior problems and lack of parental involvement in the child’s progress. There are more students that are being treated with mental illness at such an early age. She had one child that was diagnoses as a bipolar. There have been several cases of child abuse that she has had to report. She feels a challenge to education system is holding children more accountable to meet requirements verses appeasing parents. Many parents are the first to say, no it’s not my child when in fact their child is the leader of the disruptive group. Since President Bush initiated â€Å"no child left behind† program, I think this has caused challenges for the teacher to develop more creative styles of teaching without the support of administration and parents. I did not realize that the school nurse role included seven elements that they need to focus on that was listed in this week’s discussion. I thought their primary role was clinical services that included first aid and screening. After reviewing the elements, I can see this as an interdisciplinary team approach that should include teachers, lunch room staff, parents and students to ensure that students receive a top notch school health program that will provide them the tools to have a healthy lifestyle. References: United States Census Bureau. Retrieved from: http://quickfacts.census.gov/qfd/states/51/51550.html Chesapeake Public Schools, (July, 2012). School Health Advisory Board. Retrieved from: http://www.cpschools.com/shab_2012.pdf Nies, M. A., & McEwen, M. (2015). Community/Public health nursing: Promoting the health of populations (6th ed.). St. Louis, MO: Saunders/Elsevier. Chamberlain College of Nursing. (2015). NR443 Week 4: Community Health Roles, Settings, and Interventions.[online lesson]. Downers Grove, IL: DeVry Education Group Community school nurses have a very difficult job. School age children have such a variety of health concerns that can be congenital, environmental, behavioral, and socioeconomic. (Nies & McEwen, 2015) Where does a CHN start? Promoting wellness, health education, and identifying deficiencies within the schools, and creating programs to improve services is a great beginning. I do believe that most problems that we see in children and adolescents are universal. Inactivity, obesity, poor nutrition, and substance abuse are a few examples, but these problems can escalate even more when as a child’s socioeconomic condition worsens. When researching statistics I was shocked to find out that that 8.3% of teenagers in Broward County had engaged in sex before the age of 13, that is higher than the national average of 6.2%. (floridahealth.gov) To make things worse, Broward County also has the second highest rate of Infectious Syphilis in the state. HIV and Chlamydia are also on the rise compared to the rest of the United States. Sexually transmitted diseases in this demographic are increasing but teen pregnancy is on the decline. This I believe is a real problem, sex education must start in our homes with parents and transcend into our schools. According to our reading, sex education in our schools remains controversial. However, it seems like a necessity for our youth to have a nonjudgemental forum in which they can receive accurate information Wow, I was amazed at the statisctis for STD’s in Broward County and wanted to see how Chesapeake Virginia rated. Per 100,000 there was 588.3 per people diagnosed with Chlamydia and that is higher than the state of Virginina and nationally. Gonorrhea was 108.9 compared to national level of 107.5.

Study On The Annals History Essay

The Viking colonists took up the Frankish imposts manner of life so wholly that within a few coevalss of their arrival little of their Viking heritage remained. One account for this is that the figure of colonists was few and that they were rapidly absorbed into the local population. Or possibly there was a brief violent coup d'etat, after which the Vikings adopted the imposts of their neighbors out of necessity and political force per unit area. Contemporary Latin beginnings called these colonists Northmanni but this described both the Vikings and, much later, the Normans. It was a general term used to depict the Scandinavians who had become active in northern Francia in the 9th and 10th centuries. But no differentiation was made in the 10th century between the Vikings of Neustria and the Vikings in other parts of the remainder of Francia and elsewhere.A The major job with bring outing the history of the early Viking colony of Neustria is the deficiency of beginnings from the early decennaries of the 10th century, when the colony was formalised. The Vikings recorded their history subsequently and the beginnings we do hold are written by the Franks. The ulterior Norman histories are debatable because of their involvement in buttressing and legalize the baby state.A The beginnings viewed the tenth-century as a violent clip. Frankish Godheads fought for political laterality and, on the peripheries of the Frankish land, smaller groups of peoples fought for domination against each other and against the Franks. In the ninth-century, nomadic Viking forces had frequently sailed up the Seine and besieged Paris, or merely despoiled countries inside Francia. A It is difficult to state where these war-bands wintered, though it becomes clear in the annals that the additions for Viking plunderers were so great that they began to winter in Francia alternatively of returning to Scandinavia. In the early portion of the tenth-century, the Neustrian or Breton March was still regarded as portion of the Frankish land by the Franks. The Viking foraies reached their tallness during a period of instability in the Frankish lands. An component of fortune had played a portion in leting the Frankish male monarchs to govern over an undivided land for many old ages, in malice of the usage of spliting lands every bit between boies on the decease of their male parent. Peppin the Short, Carloman his boy and Charlemagne his grandson ruled over an unbroken land. But on the decease of Charlemagne ‘s boy Louis the Pious in 840, Francia was at last split. There was a period of atomization, with Francia divided into three lands: West Francia, Lotharingia, and East Francia. Charles the Simple, King of West Francia ( subsequently to go France ) from 898 to 922, regained pre-eminence in the Frankish lands after this period of battle, though other cabals existed. It was this political insta bility that Viking leaders exploited as they fought and befriended their Frankish opposite numbers.How make the histories assist?Historians who attempt to retrace the early history of Normandy face a figure of jobs. The beginnings are few and, worse still, their truth is frequently to be doubted. Palgrave warned that â€Å" if you accept the undertaking you must accept Dudo or allow the work entirely. † Today, the history of Dudo of St Quentin is viewed with so much intuition by historiographers that, even where his history runs with other modern-day authors, he is still distrusted. But without Dudo we have small grounds. The Frankish historian Flodoard of Reims[ 1 ]provides some information about Normandy in the first half of the ninth-century, there are a few mentions to early Normandy in Norse beginnings and even a late Welsh beginning. Later Norman beginnings for this period do be, but many of these are based on Dudo ‘s history, so must be treated with cautiousness. With such a deficiency of literary stuff, historiographers are left with the consequences of research from archeology and analysis of place-name. The reading of archeological grounds is hard and the decisions that can be drawn from it can be even more obscure than literary beginnings. The historiographer ‘s undertaking in chronicling early Norman history is therefore a hard one, and the decisions reached are, by necessity, limited in nature. Dudo of St Quentin was born c. 960 in Vermandois. He wrote De moribus et actis primorum Normanni? ducum ( The Deeds of the Early Dukes of Normandy ) from approximately 996 to the clip he became Dean of St Quentin in 1015. The earlier history, including some extremely questionable and fictional inside informations, was based on Virgil ‘s Aeneid and Jordanes ‘ Getica. His chief source for the inside informations of his history was Count Rodulf of Ivry. Commissioned originally by Duke Richard I, the history ended with the decease of Richard in 996. Dudo appears to cognize a great trade about Rollo, and he is the lone beginning for the Treaty of Saint-Clair-sur-Epte, where Charles the Simple granted Rollo the lands around Rouen in 911. Rollo is baptised and, in return, receives the grant of land. The bishops said to Rollo, who was unwilling to snog King Charles ‘s pes: â€Å" You who receive such a gift ought to snog the male monarch ‘s pes. † And he said: â€Å" I shall ne'er flex my articulatio genuss to another, nor shall I kiss anyone ‘s pes. † Compelled, nevertheless, by the supplications of the Franks, he ordered one of his soldiers to snog the male monarch ‘s pes. The adult male instantly seized the male monarch ‘s pes, put it to his oral cavity and kissed it while the male monarch was still standing. The male monarch fell level on his dorsum. This raised a great laugh and greatly stirred up the crowd. â€Å" A A great narrative, but about surely a fable. Dudo was the official chronicler of the Rollonid dynasty, and he portrays Rollo as the leader of the Vikings in many runs and conflicts, possibly excessively many for historiographers to believe it. The facts of Rollo ‘s early old ages as leader of the early Normans a re hence lost in the semblance of ulterior myths. Nonetheless, some of the indispensable inside informations in Dudo ‘s narrative have some cogency. Though Dudo is the lone beginning who dates the understanding between Rollo and Charles at 911, this does look to be a extremely plausible day of the month for the understanding. It is ill-defined when Viking plunderers began to settle in the coastal country, but there is some grounds from the few paperss that survive from this period. A Carolingian charter of 905 records Charles the Simple ‘s grant of two helot of the Crown from the pagus of Rouen to his Chancellor of the Exchequer Ernestus. This was the last royal charter in Normandy.A Three months subsequently, some thought of the convulsion in the part can be concluded from a charter of 906 that records the transportation of relics from Saint-Marcouf ( now in Manche, Basse-Normandie ) to Corbeny â€Å" because of the inordinate and drawn-out onslaughts of the heathens. â€Å" A A In 918, Charles the Simple granted the lands of the old abbey of La Croix-Saint-Leufroi to the abbey of Saint-Germanin-des-PresA â€Å" except that portion of the abbey ‘s lands that we have granted to the Normans of the Seine, viz. to Rollo and his followings, for the defense mechanism of the land. † A The p act entering this land grant to Rollo no longer exists, but it is clear that between the day of the months of these two royal announcements, Rollo and his followings had established themselves. The decisive event may hold been a conflict at Chartres in 911. Later Norman tradition tends to hold with this and places Rollo at the Centre of events, though some historiographers question this. One reading of the beginnings is that as a consequence of this conflict, the Vikings were appeased with a grant of land in order to incorporate and command them. Flodoard of Reims tells us that the Vikings had been granted the lands around Rouen â€Å" had some clip ago been given to the Northmen on history of the pledges of Charles who had promised them the comprehensiveness of the state. † Flodoard ‘s history is of import because it appears to give a modern-day position of the period. He was a canon of Reims, and wrote his annals from c. 925 until his decease in 966. The lone job is that he was some distance from Normandy, and the history of Normandy was non his chief concern. It is clear from his history that the Vikings and the Franks were in changeless battle. In 925, Flodoard records that â€Å" the Normans of Rouen broke the pact which they had one time made and devastated the territories [ pagi ] of Beauvais and Amiens. Those citizens of Amiens who were flying were burned by a fire for which they were ill-prepared. † The Franks responded by looting Rouen: â€Å" they set fire to manors, stole cowss and even killed some of the Normans. † Count Herbert led another force against the Vikings towards the E, and surrounded them in a cantonment on the coast.A A â€Å" It was this really same cantonment, situated on the seashore and called Eu that the Franks surrounded. They broke through the bulwark by which the cantonment was surrounded in forepart of its walls and weakening the wall, climbed all. Once they had won ownership of the town by contending, they so slaughtered all the males and put fire to its munitions. Some, nevertheless, escaped and took ownership of a certain neighbouring island. But the Franks attacked and captured it, although with a greater hold than when they had seized the town. After the Normans, who had been continuing their lives by contending as best they could, had seen what had happened and had let steal any hope of endurance, some plunged themselves into the moving ridges, some cut their pharynxs and some were killed by Frankish blades, while others died by their ain arms. And in this manner, one time everyone had been destroyed and an hideous sum of loot had been pillaged, the Franks returned to their district. † This graphic description gives historians a sense of the force of the age. The Vikings were marauding all across the northern coastal parts of Francia, though Neustria does look to be the chief country of their colony. However, they were surely non confined to this country, or prepared to accept its boundaries. In 937, Flodoard tells us, â€Å" The Bretons retreated to their fatherland after their long peregrinations fought in frequent conflicts with the Normans, who had invaded the district which had belonged to them, next to their ain. They ended up the stronger in many of these conflicts and reclaimed their ain district. â€Å" A Rollo is mentioned in 925 as princeps ( leader ) of the Northmen at Rouen. Although non mentioned at the clip, grounds from the 918 charter strongly suggests that the Norman chroniclers are right in stating that Rollo led the ground forces from the start. However, Dudo ‘s mention to the Treaty of St Clair-sur-Epte is unsubstantiated and should be dismissed as undependable. Dudo was besides misdirecting when depicting the footings of the colony. The granting of â€Å" the land from the river Epte † runs with the other beginnings, but the granting of Brittany does non. Neither does the scene of the arrant wilderness clasp true: if the land granted by Charles to the Vikings was â€Å" uncultivated by the plowshare, wholly deprived of herds of cowss and flocks of sheep and lacking in human life † , so why do Norse place-names merely form a minority of all place-names throughout Normandy? Entertaining though Dudo ‘s narrative may be, his history, and those of his followings and impersonators, can non be trusted for the early history of Normandy and historiographers must vacate themselves to set uping a few bare facts in the thick of ulterior deformations. The extension of Normandy ‘s boundary lines can be seen in Flodoard ‘s history. A King Ralph conceded Bayeux and Maine [ Cinomannis et Baiocae ] in 925 harmonizing to Flodoard, though there are uncertainties about the grant of Maine. Later in 933, the Normans were given Avranchin and Cotentin. Excluding Maine, this established Normandy in the approximative signifier that it existed in 1066. A The Cotentin peninsula was besides settled by Vikings independently of the Vikings under Rollo at Rouen. These early old ages were violent times. The Normans were invariably warring, contending with the Franks in 923, but chiefly concerned with spread outing their ain domain of influence. The people of Bayeux revolted against Viking regulation in 925, a twelvemonth after they had been transferred to the control of the counts of Rouen. Dudo recalls a rebellion against William Longsword by a certain Riulf: â€Å" ferociously filled with ill-famed perfidiousness † . Against all the emphasiss and the strains, against internal rebellion and external menaces, Normandy had secured its place by the center of the tenth-century and, though its security was threatened many times, the Norman district was strongly governed and able to throw off its enemies. This might possibly take us to see the pacts between the Franks and the Vikings as more important than they were at the clip. All the grounds suggests that the boundaries were comparatively unstable. Agreements were made, and Vikings baptised, but these baptisms frequently proved impermanent personal businesss. In the 920s, the archbishops of Rouen and Reims both wrote letters on the topic of Vikings who remained heathen despite holding converted. Herveus of Reims asked the Pope: â€Å" What should be done when they have been baptised and re-baptised, and after their baptism continue to populate in heathen manner, and in the mode of heathens kill Christians, slaughter priests, and, offering forfeits t o graven images, eat what has been offered? † There is small grounds for the widespread debut of Norse establishments or life style. Although in 1013 Duke Richard II welcomed a group of Vikings at Rouen, excessively much should non be read into this. The leaders, Richard and Olaf, may hold felt some commonalty, but this can non be discovered. Merely as Frankish Lords and male monarchs had welcomed Vikings and baptised them as Christians, in the hope of change overing them into a friend and non doing them an enemy, so Richard did with Olaf and his Vikings. Olaf had ravaged Brittany, but had allowed himself to be converted by Richard. The Normans were truly now more Franks than Scandinavians. Dudo claims that at the clip of William Longsword, Scandinavian address was disused at Rouen, and it is so likely that the native lingua was shortly adopted. On the Eve of the first Crusade, the Norman knight Bohemond was able to inquire, rhetorically, â€Å" Are we non Franks? †How does archeological and place-name grounds aid?The lan d divisions in Normandy appear to hold remained unchanged from the Frankish to the Norman eras. Jacques Le Maho ‘s survey of the Pays de Caux shows a continuity of seigneurial abodes, and it has been argued that there was greater continuity in this part than in other parts of Francia. The Vikings did convey bondage with them, but this did non last beyond the first century of business. The Normans seems to hold been extremely integrated with the Franks. One piece of grounds for this is the Fecamp coin host, including some coins struck at batchs in Cologne, Arles and Pavia. In Scandinavia, Norman coins discontinue to look in hosts after the early 11th century, looking alternatively in Francia and Italy. This suggests a continuance of merchandising links with Scandinavia for a piece, but with a steadily increasing Norman accent on contacts with the continent. Frankish justness was adopted ; the Norse thing did non go established. The survey of place-names provides an penetration into early Normano-Viking colony. The comprehensive survey undertaken by Jean Adigard des Gautrie tells the narrative of the Viking inflow. Taking all place-names with a possible or definite Norse influence, it can be seen that these are particularly legion in the Cotentin peninsula and along the seashore, with another big bunch in the Pays de Caux. They were besides legion â€Å" all along the great invasion path that was the Seine † and down the other rivers as good: grounds of the Vikings transporting on their raiding, going by ship across sea and along rivers. It seems rather likely that when Rollo had his territorial claims to Neustrian March recognised, he based his disposal around a coastal group of colonies already in being due to the activities of other Vikings over a figure of old ages. However, Norse place-names ne'er formed a local bulk over preexistent Frankish names, even in the countries of highest Norse place-name denseness. One account for this is the fleet acceptance of the local lingua by the Normans. Frank Stentonhttp: //www.manshead.beds.sch.uk/History/AS and A Level/The Normans in Europe/Normandy/Founding Normandy/when_did_the_vikings_become_norm.htm – _ftn10 made a good point when he compared place-names in Normandy and the English Danelaw. He pointed out that place-names with Viking personal name elements besides had Norse postfixs, for illustration Grimsby: the Viking personal name Grim and the postfix -by, the Norse word for small town. He compared this to Normandy, where place-names that have Viking personal names really frequently have native terminations, for illustration, A Gremonville, the stoping of which comes from the Latin Villa. The former indicates a big colony of Vikings, who named topographic points in their ain lingua. The latter might merely demo that while the Viking incomers founded and took over topographic points, it was the local population who really named these topographic points. This could be an indicant of the extent of the Viking colony in N ormandy. Archaeological grounds can state us small about early colony. Patrick Perik, analyzing the grounds found around the lower Seine, admits that the â€Å" archeological certification is singularly thin. † There is grounds for Norse presence: Viking blades and axes have been found, although Perin points out that despite two discoveries in the land that were likely buried as portion of a funeral, the weaponries found were all in the river. While this shows that Vikings were present here, it is non clear whether the discoveries are chiefly from colonies or chiefly from marauding hosts before the colony epoch. This grounds adds little to our cognition. It is clear that Northmen were present in Normandy for a long clip, but the archeology is scarce and can non be pinpointed in clip to give a clearer image of the early old ages of the Viking colony. The deficiency of discoveries does non problem David Bates unduly, though. â€Å" If an extended colonization can be argued for in Englan d despite the absence of important archeological discoveries, so the same decision seems executable for Normandy. † The deficiency of Viking discoveries does non automatically dismiss a ample Viking colony, but if this was the instance so the colonists really rapidly adopted Frankish imposts. Whatever the size of the colony, there is another argument on the velocity of integrating. â€Å" Whichever manner we turn † , writes Ralph Davies, â€Å" we have to acknowledge that the Viking society of Rollo and his comrades was something rather different from the Norman society of the 11th century. The one developed from the other, but the development was non effectual until the two races had merged and the Northmen had, for all practical intents, become Frenchmen. † The degree of integrating is hard to state, and David Bates and Eleanor Searle keep different positions on this. Bates believes that the Viking incomers rapidly became integrated into the native society, so that they had shortly adopted Frankish manners and establishments. Searle ‘s place is that they remained self-consciously Viking until the mid-eleventh century. The grounds for this period is patchy and frequently inconclusive. The early history of Normandy can be told magisterially merely in really au naturel and apparent footings. Tempting though it is to utilize more expansive and colorful Norman paperss, these tell us more about the demands of the developing Norman province than about its early history. For the period he records, 923-966, Flodoard of Reims seems to be a dependable beginning, though his chief focal point is non Normandy. As for the Norse impact on Normandy, there does non look to hold been an overpowering turbulence. Norse linguas appear non to hold been spoken more than three coevalss after the colony. Administrative territories were kept integral, estates seem to hold survived, and on the whole the Normans ruled through Frankish-style establishments. But Michel de Bouardhttp: //www.manshead.beds.sch.uk/History/AS and A Level/The Normans in Europe/Normandy/Founding Normandy/when_did_the_vikings_become_norm.htm – _ ftn14 warns against the simple premise of continuity merely because of a deficiency of institutional alteration. He talks of the â€Å" energy, the effectivity of ducal power in Normandy † and warns that we should ne'er bury the â€Å" human factor † in all this. Surely, Normandy grew as a power once the Vikings had taken control. There is grounds here for both continuity and discontinuity. Since the beginnings tell us so small, it is a argument that will be difficult to decide.