Accomplice Liabilty Essays - Criminal Law, Elements Of Crime

Accomplice Liabilty Questions Presented 1. Whether a person in Alaska can be charged as an accomplice to an unintentional crime, when Alaskan courts required that one must have the specific intent to promote or facilitate the offense? 2. Whether the mother was the legal cause of her childrens death, when she permitted the father to take the children in his car when he was drunk? Statement of the Case The appellant, Elaine Benis, was indicted in the County of Norchester, on one count of manslaughter, pursuant to A.S. ?11.41.120. (R. at 1.) She was also indicted for one count of accessory to manslaughter, pursuant to A.S. ?11.41.120 and A.S. ?11.16.110. (R. at 1). After the presentation of the prosecutions case, the defense moved to dismiss on the grounds that the prosecution did not prove beyond a reasonable doubt that Mrs. Benis was reckless. (R. at 9). This motion was denied. At the conclusion of its case, the defense moved for a directed verdict, stating that the prosecution failed to show that Mrs. Benis recklessly caused the death of her children. (R. at 12). This motion was denied and the judge informed the counselors that he would charge the jury in accordance with the states proposed charge. (R. at 13). The defense strongly objected and renewed its motion for a directed verdict, submitting that there was insufficient evidence to prove that Mrs. Benis was the cause of her c hildrens death, since Mr. Petermans actions clearly were the only cause of their death and that it is logically impossible for any jury to find someone guilty as an accomplice to an unintended crime. (R. at 13). The trial judge denied the motion. (R. at 13). Mrs. Benis was convicted and appealed to the Court of Appeals of the State of Alaska. (R. at 15). At issue in the appeal was whether the trial court erred, as a matter of law, (1) in instructing the jury on the charge of accessory to manslaughter and (2) in denying Mrs. Beniss post trial motion for a directed verdict because there was insufficient evidence to support a conviction as a principal. (R. at 16). The Court of Appeals held that the trial court did not err in instructing the jury that one can be an accomplice to reckless manslaughter even though it is a not a specific intent crime. (R. at 17). The court based its decision on holdings from other jurisdictions and rejected the Alaskan doctrine that one cannot be an accomplice to a crime when he acts recklessly. (R. at 17). Furthermore, the court held that there was sufficient evidence to support a conviction of Mrs. Benis as principal because her act was the legal cause of death. (R. at 17). Mrs. Benis now appeals to the Supreme Court of Alaska. This appeal is limited to the issue of whether being an accessory to manslaughter is a crime under Alaska law and whether there was sufficient evidence that Mrs. Beniss act caused the death of her two daughters. (R. at 19). The defense appeals on the grounds that the law of Alaska does not permit an instruction that one can be an accomplice to an unintentional crime when they did not have the specific intent to promote or facilitate the offense and that Mrs. Beniss act was not the proximate cause of her two childrens death. On Sunday, October 10, 1999, Jay Peterman came to his wifes house, Mrs. Benis, because he is allowed to see his children, pursuant to a temporary separation agreement. (R. at 16). Mrs. Benis testified that her husbands eyes were red and that he appeared tipsy, but he drove up to the house, so I thought he was O.K. (R. at 11). However, when the prosecution asked Mrs. Benis if she knew that Mr. Peterman was drunk at the time he picked up the girls, she emphatically replied No. (R. at 12). Furthermore, expert testimony from the Medical Examiner reveals that even though someone has a blood alcohol level of 0.14, it is not absolutely certain that the person appears intoxicated to the outside world. (R. at 7). Mr. Peterman had a breath-analyzing device installed in his car because of past drunk driving incidents. (R. at 16). This

Multivariate Econometrics Problems and Excel

Multivariate Econometrics Problems and Excel Most economics departments require second or third year undergraduate students to complete an econometrics project and write a paper on their findings. Years later I remember how stressful my project was, so Ive decided to write the guide to econometrics term papers that I wish I had when I was a student. I hope that this will prevent you from spending many long nights in front of a computer. For this econometrics project, Im going to calculate the marginal propensity to consume (MPC) in the United States. (If youre more interested in doing a simpler, univariate econometrics project, please see How to Do a Painless Econometrics Project) The marginal propensity to consume is defined as how much an agent spends when given an extra dollar from an additional dollars personal disposable income. My theory is that consumers keep a set amount of money aside for investment and emergency, and spend the rest of their disposable income on consumption goods. Therefore my null hypothesis is that MPC 1. Im also interested in seeing how changes in the prime rate influence consumption habits. Many believe that when the interest rate rises, people save more and spend less. If this is true, we should expect that there is a negative relationship between interest rates such as the prime rate, and consumption. My theory, however, is that there is no link between the two, so all else being equal, we should see no change in the level of the propensity to consume as the prime rate changes. In order to test my hypotheses, I need to create an econometric model. First well define our variables: Yt is the nominal personal consumption expenditure (PCE) in the United States.X2t is the nominal disposable after-tax income in the United States. X3t is the prime rate in the U.S. Our model is then: Yt b1 b2X2t b3X3t Where b 1, b 2, and b 3 are the parameters we will be estimating via linear regression. These parameters represent the following: b1 is the amount the level of PCE when nominal disposable after-tax income (X2t) and the prime rate (X3t) are both zero. We do not have a theory about what the true value of this parameter should be, as it holds little interest to us.b2 represents the amount PCE rises when the nominal disposable after-tax income in the United States rises by a dollar. Note that this is the definition of the marginal propensity to consume (MPC), so b2 is simply the MPC. Our theory is that MPC 1, so our null hypothesis for this parameter is b2 1.b3 represents the amount PCE rises when the prime rate increases by a full percent (say from 4% to 5% or from 8% to 9%). Our theory is that changes in the prime rate do not influence consumption habits, so our null hypothesis for this parameter is b2 0. So we will be comparing the results of our model: Yt b1 b2X2t b3X3t to the hypothesized relationship: Yt b1 1*X2t 0*X3t where b 1 is a value that does not particularly interest us. To be able to estimate our parameters, well need data. The excel spreadsheet Personal Consumption Expenditure contains quarterly American Data from the 1st quarter of 1959 to the 3rd quarter of 2003. Â  All data comes from FRED II - The St. Louis Federal Reserve. Its the first place you should go for U.S. economic data. After youve downloaded the data, open up Excel, and load the file called aboutpce (full name aboutpce.xls) in whatever directory you saved it in. Then continue to the next page. Be Sure to Continue to Page 2 of How to Do a Painless Multivariate Econometrics Project Weve got the data file open we can start to look for what we need. First we need to locate our Y variable. Recall that Yt is the nominal personal consumption expenditure (PCE). Quickly scanning our data we see that our PCE data is in Column C, labeled PCE (Y). By looking at columns A and B, we see that our PCE data runs from the 1st quarter of 1959 to the final quarter of 2003 in cells C24-C180. You should write these facts down as youll need them later. Now we need to find our X variables. In our model we only have two X variables, which are X2t, disposable personal income (DPI) and X3t, the prime rate. We see that DPI is in the column marked DPI (X2) which is in Column D, in cells D2-D180 and the prime rate is in the column marked Prime Rate (X3) which is in column E, in cells E2-E180. Weve identified the data we need. We can now compute the regression coefficients using Excel. If you are not restricted to using a particular program for your regression analysis, Id recommend using Excel. Excel is missing a lot of the features a lot of the more sophisticated econometrics packages use, but for doing a simple linear regression it is a useful tool. Youre much more likely to use Excel when you enter the real world than you are to use an econometrics package, so being proficient in Excel is a useful skill to have. Our Yt data is in cells E2-E180 and our Xt data (X2t and X3t collectively) is in cells D2-E180. When doing a linear regression we need every Yt to have exactly one associated X2t and one associated X3t and so on. In this case we have the same number of Yt, X2t, and X3t entries, so were good to go. Now that we have located the data we need, we can calculate our regression coefficients (our b1, b2, and b3). Before continuing you should save your work under a different filename (I chose myproj.xls) so if we need to start over we have our original data. Now that youve downloaded the data and opened Excel, we can go onto the next section. In the next section we calculate our regression coefficients. Be Sure to Continue to Page 3 of How to Do a Painless Multivariate Econometrics Project Now onto the data analysis. Go to the Tools menu on the top of the screen. Then find Data Analysis in the Tools menu. If Data Analysis is not there, then youll have to install it. To install the Data Analysis Toolpack see these instructions. You cannot do regression analysis without the data analysis toolpack installed. Once youve selected Data Analysis from the Tools menu youll see a menu of choices such as Covariance and F-Test Two-Sample for Variances. On that menu select Regression. The items are in alphabetical order, so they shouldnt be too hard to find. Once there, youll see a form that looks like this. Now we need to fill this form in. (The data in the background of this screenshot will differ from your data) The first field well need to fill in is the Input Y Range. This is our PCE in cells C2-C180. You can choose these cells by typing $C$2:$C$180 into the little white box next to Input Y Range or by clicking on the icon next to that white box then selecting those cells with your mouse. The second field well need to fill in is the Input X Range. Here we will be inputting both of our X variables, DPI and the Prime Rate. Our DPI data is in cells D2-D180 and our prime rate data is in cells E2-E180, so we need the data from the rectangle of cells D2-E180. You can choose these cells by typing $D$2:$E$180 into the little white box next to Input X Range or by clicking on the icon next to that white box then selecting those cells with your mouse. Lastly well have to name the page our regression results will go on. Make sure you have New Worksheet Ply selected, and in the white field beside it type in a name like Regression. When thats completed, click on OK. You should now see a tab on the bottom of your screen called Regression (or whatever you named it) and some regression results. Now youve got all the results you need for analysis, including R Square, coefficients, standard errors, etc. We were looking to estimate our intercept coefficient b1 and our X coefficients b2, b3. Our intercept coefficient b1 is located in the row named Intercept and in the column named Coefficients. Make sure you jot these figures down, including the number of observations, (or print them out) as you will need them for analysis. Our intercept coefficient b1 is located in the row named Intercept and in the column named Coefficients. Our first slope coefficient b2 is located in the row named X Variable 1 and in the column named Coefficients. Our second slope coefficient b3 is located in the row named X Variable 2 and in the column named Coefficients The final table generated by your regression should be similar to the one given at the bottom of this article. Now youve got the regression results you need, youll need to analyze them for your term paper. We will see how to do that in next weeks article. If you have a question youd like answered please use the feedback form. Regression Results Observations Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept X Variable 1 X Variable 2 -13.71941.4186-9.67080.0000-16.5192-10.9197

Just War Theory and How It Relates to Desert Storm and the War in Research Paper

Just War Theory and How It Relates to Desert Storm and the War in Afghanistan - Research Paper Example Operations Desert Storm or Gulf war was conducted during 17 January 1991 – 28 February 1991, between an UN-authorized coalition forces from 34 nations against Iraq. The UN coalition forces were headed by America and the reason for this war was Iraq’s invasion of Kuwait. George Bush Sr. was the American president at that time. The current Afghan war was started in 2001, immediately after the 9/11 incident. This war is often labeled as war on terror and the reason cited for this war was that terrorists use Afghan soil for conducting violent activities across the world. Taliban was accused for keeping nexus with other terrorist organizations in the world. In other words, America suspects that Taliban, Al Qaida and other terrorist organizations are working against America from Afghan soil. Politicians and neutral observers have different opinions about operation desert storm and Afghan war. Some people support these wars whereas others oppose it. This paper analyses operati on desert storm and Afghan war in terms of just war theory. Historically, the just war tradition may be said to commonly evolve between two culturally similar enemies. That is, when an array of values are shared between two warring peoples, we often find that they implicitly or explicitly agree upon limits to their warfare. But when enemies differ greatly because of different religious beliefs, race, or language, and as such they see each other as â€Å"less than human†, war conventions are rarely applied (Mosely). Gulf War took place between two culturally similar countries. Muslims or Arabs in Kuwait and Iraq have same religious beliefs and customs. There are plenty of similarities between Iraqis and Kuwaitis. Under such circumstances, one can definitely conclude that just war theory is definitely applicable to Gulf war. On the other hand, war in Afghanistan is taking place between Christian dominated America and Muslim dominated Taliban or Afghan people. Even though Muslim s and Christians do have a common father in Abraham (Jewism, Islam and Christianity are three Abrahamic religions), their beliefs and customs are entirely different. Christians believe that Jesus the saviour of human kind whereas Muslims believe that Prophet Mohammad is the saviour of humans. In short, Afghan war cannot be included under the just war theory since two culturally different parties are fighting each other here. â€Å"It has been the concern of the majority of just war theorists that the lack of rules to war or any asymmetrical morality between belligerents should be denounced, and that the rules of war should apply to all equally† (Mosely). Saddam’s ambitions to expand Iraq’s territory were resulted in Gulf War. Iraq failed to accept Kuwait as a sovereign state and they tried to conquer it using muscle power. Saddam argued that Kuwait is part of Iraq historically and it should be added to Iraq’s territories. On the other hand, international community was not convinced by these arguments and the result was Gulf War. On the other hand, 9/11 caused war on terror and Afghan war. America started two war fronts; one in Afghanistan and another in Iraq immediately after the 9/11 incident. America believed that Saddam has joined hands with Al Quaid leader Osama to conduct terrorist activities in America. In their opinion, the Taliban dominated Afghanistan was the origin of all