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The Effects Of Unemployment On The United States - 942 Words

Over the course of many years the United States has done a very good job of creating and supplying jobs for the citizens. This could be an effect of our economic standings or is there a reason other countries do better than others? There are many countries that are doing better than the United States in the aspect of unemployment, but the US currently has a very low rate of 4.8% (List of Countries). The country that is currently doing the best is Qatar with a rate of 0.4%. This could be for many reasons such as population (List of Countries). One thing that I have found is that there is a direct correlation to standard of living and unemployment rate. Many of the poorer countries in the world have a much higher unemployment, such as†¦show more content†¦When the country goes through depression most of the time the rate will rise dramatically and go back down. This has happened many times, the most recent only being four to five years ago. The unemployment rate is currently 4 .8%, which is a good place to be. This has been the average rate in the US for a very long time. This is an effect of our strong economy. Economy is described as the wealth and resources of a country, especially in terms of production and consumption of goods and services. The economy is also determined by population and standard of living. If the population is very high in a country and standard of living is low, then the unemployment rate will most likely be very high. This goes both ways. The United States has a very good standard of living and a population of around 326 million, this affects the economy making the unemployment rate what it is. There are some countries that are doing a better job of this but most have a higher rate than the US. Most countries with poor economic systems have high unemployment rates such as Zimbabwe, Syria and Yemen. All of these countries are close in population but are low in comparison the US. They also have very low standards of living and very high rates. There are other cases like Qatar with a population of around two million and with the lowest unemployment rate. It varies from country to country. China has a population of over one billion and has around theShow MoreRelatedUnemployment And Its Effects On The United States1443 Words   |  6 PagesThe United States is full of amazing things, historic landmarks, pizza, Nascar and countless other things that help set our nation apart. However there is one thing that our nation shares with every other nation in the world that isn’t so great, in fact many people would agree it is one of the worst things for a nation to have. No it’s not smallpox, it’s unemployment. Unemployment is unfortunately something a nation cannot vaccinate against. Sadly nations are always going to experience unemploymentRead MoreA Brief Note On Unemployment And Its Effects On The United States Essay1902 Words   |  8 Pages†¢ Unemployment Deferment – 12 months per Request (interest accrues monthly) maximum number allowed: up to 36 months/life of the loan. The Borrower has to submit evidence of receiving unemployment benefits/verify employment agency enrollment/show proof of previously granted Unemployment Deferment through another servicer. †¢ Economic Hardship Deferment – 12 months per Request (interest does not accrue) maximum number of months allowed: up to 36 months/life of the loan. The Borrower has to submitRead MoreThe Effects Of Unemployment On The Economy1656 Words   |  7 Pagesleading problems not only just in the United States but also around the world. One of the major problems faced in different economies all around the world is unemployment. Even though the idea of unemployment may seem to be a usual day-to-day problem, the effects of unemployment are adverse on the health and well being of an economy In the United States; unemployment has been fairly low (5% or lower) for much of the past two decades. However even a low unemployment rate affect and undermine economicRead MoreLosing More Than A Job : Effects Of Long Term Unemployment On The Average American Essay1543 Words   |  7 PagesLosing More Than a Job: Effects of Long-Term Unemployment on the Average American Job loss can happen to anyone, but when being without work stretches over months— even years—it can be challenging to survive it. Long-term unemployment, defined as being out of work for six months or longer, has a myriad of effects on the average American; it impacts not only their economic well-being, but their mental and physical health. Finances can suffer, self- worth can plummet, and health can deteriorate.OnRead MoreEconomic Crisis: Effects on the Economy1486 Words   |  6 PagesRunning Head: ECONOMIC CRISIS: EFFECTS ON THE ECONOMY 2 Abstract The United States is obviously in a state of economic despair. This essay has supporting facts that prove the economy is definitely not on the mend. The public has been led to believe that this downward spiral is almost over. What will be proven in this paper is that foreclosure rates are still dramatically increasing and that the total in unemployment rates is deceiving. Without more jobs, consumersRead MoreMacro And Micro Of Sweden And United States811 Words   |  4 Pagesand Micro of Sweden and United States What is Macroeconomics? Macroeconomics is the part of economics study that looks at the operation of a nation’s economy as a whole (30). Macroeconomics main focus is the production and consumption in an economy. Economists that specialize in macro investigate the effects of general taxes such as income and sales taxes output and prices. They also study the causes of economic upswings and downturn and the effects of monetary and fiscalRead MoreUnemployment And Its Effects On America926 Words   |  4 PagesIn the United States, nearly all of the citizens are trying to look online or the newspaper to find jobs, so they can’t get nutritious food, medical care, have warm clothing, and have a roof over their heads. Half of the unemployed people are homeless, they are going through the smelly, dirty trash bins to get food in their stomachs and also their kids (if they have any). They are live in small,brown, moldy cardboard boxes or sleeping wherever they can to survive. There are about 5.5 percent of peopleRead MoreThe Real Causes of the Depression1020 Words   |  5 PagesStatistics show right now in the United States the unemployment rate is high. A lot of people are saying that this is bad and the economy is slowly going downhill, but most people forget to think that these things are normal and is nothing worse than the Depression of the 1930s. Although some people say that the Depression was caused by the Smoot-Hawley Tariff Act, it was strictly due to many reasons that were unrelated to the Act. The Smoot-Hawley Tariff Act was signed by President Herbert HooverRead MoreThe European Crisis Of Greece, Spain, And The United States1587 Words   |  7 Pagescrisis created unstable economic and social situations in many countries. The Eurozone crisis negatively affects Greece, Spain, and the United States. First, the European Union crisis elicited a health crisis in Greece. Second, the European Union crisis caused unemployme nt and stress in Spain. Third, the EU crisis generates negative implications for the United States’ economy. Evidently, the fall of Europe’s economy caused severe impacts on surrounding countries. The European debt crisis createdRead MoreUnemployment Rate Of The United States1719 Words   |  7 PagesBrandon Phan Phan 1 Ms. Barrett English 5 20 November 2015 Rough Draft With an unemployment rate of 5% and a population of about 326,079,646 people, there can be about 163,039,823 unemployed people in the United states. There are many things that the United States government can do to reduce Unemployment. In order to reduce the unemployment rate in the United States, the United States government could reduce the federal minimum wage to allow employers to hire more employees because of

Time Series Free Essays

A time series is a set of observations, xi each one being recorded at a specific time t. After being recorded, these data are rigorously studied to develop a model. This model will then be used to produce future values, in other words, to make a forecast. We will write a custom essay sample on Time Series or any similar topic only for you Order Now Important Characteristics to Consider First When first looking at a time series, some questions must be asked:Does the time series has a trend or seasonality over time?Are their outliers? With time series data, the outliers are far away from the other data.Is there a long-run cycle or period?Is there constant variance over time? Essential of Good time series Data must be for a sufficient period Equal time ga Constant or normal period. Example1The following plot is a time series plot of the annual number of earthquakes in the world with seismic magnitude over 7.0, for 99 consecutive years. By a time series plot, we simply mean that the variable is plotted against time.Some features of the plot:There is no trend.The mean of the series is 20.2There is no seasonality as the data are annual data.There are no outliers. Example 2 The plot at the top of the next page shows a time series of quarterly production of beer in Australia for 18 years.Some important features are:There is an increasing trend.There is seasonality.There are no obvious outliers.The Components of Time SeriesThe components of time series are factors that can bring changes to the time series:Trend component, TtWhen there is an increase or a decrease over a long period of time in the data, then we say that there is a trend. Sometimes, a trend is said to be changing direction when it goes from an increasing trend to a decreasing one. It is the result of events such as price inflation, population growth or economic changes.Seasonal component, StA seasonal pattern exists when the time series exhibits regular fluctuations at specific time. It arises from influences such as natural conditions or social and cultural behaviors. For example, the sales of ice-cream are relatively high in summer. So, the salesman expects greater profit in summer than in winter. Cyclic component, CtIf the time series shows an up and down movement around a given period of time, it is said to have a cyclical pattern.Irregular component, ItIrregular components consist of changes that are unlikely to be repeated in a time series. Examples are floods, fires, earthquakes or cyclones.Combining the time series componentsTime series is a combination of the components which were discussed above. These components can be either combined additively or multiplicatively.Additive modelIt is linear, and the changes are made by the same amount over time.Yt = Tt + Ct + St + ItMultiplicative modelIt is non-linear such as quadratic or exponential, and the changes increase or decrease over time. Yt = Tt Ãâ€"Ct Ãâ€" St Ãâ€" ItUsesTime series can be useful in the following fields:StatisticsSignal processingEconometricsMathematical financeAstronomyEarthquake predictionsWeather forecastingImportance of Time series for businessesThere are many benefits of time series for business purposes:Helpful for study of past behaviorBusinessmen use time series to study the past behaviors and to see the trend of the sales or profit of their businesses. Helpful in forecastingTime series is a great tool for forecasting. Businesses can make a time series of the past strategies of their competitors and make an estimate of their future strategies. In this way, they make can built a better strategy and make more profits.Helpful in comparisonTime series can be used to calculate the trend of two or more branches of the same company and compare their performance. On their performances, rewards can be given. However, time series can have some limitations for a business. Sales forecasting relies on the past results to predict future expectations. But, if a company is new, there is a limited amount of data to make predictions. Even so, past results do not always indicate what the future sales will be.To fully understand this topic, we will work out this example.Example 2We will consider the actual arrival of passengers from an airport over the year 1949 to 1960. From these data, we will make a forecast. The first step is to plot the data and obtain descriptive measures such as trends or seasonal fluctuations.The second step is to check for the stationarity of the time series.StationarityA time series is said to be stationary if its mean and variance does not change over time. Obviously, not all the time series that we encounter are stationary. It is important because, most of the models we work on, assumes that the time series is stationary. If the time series has the same behavior over time, there will be a high probability that it will follow the same trend in the future.How to check for stationarity?For the graph that was plotted, we can see that it has an increasing trend with some seasonal pattern. But, it is not always evident to see whether a plot is increasing or has a seasonal trend. We can check for stationarity using the following:Plotting rolling statisticsWe plot the moving average or variance and see whether it changes with time. But, as it is a visual technique, we will take more consideration for the next test.Dickey-Fuller testIt is one of the statistical methods to check for stationarity. The null hypothesis is that the time series is non-stationary, and the alternative hypothesis is the converse.As shown below, the test consists of the test statistics and critical values at different significant levels. If the test statistics is less than the critical value, we reject the null hypothesis. Results of Dickey-Fuller Test: Test Statistic 0.815369p-value 0.991880#Lags Used 13.000000Number of Observations Used 130.000000Critical Value (1%) -3.481682Critical Value (5%) -2.884042Critical Value (10%) -2.578770According to the Dickey-Fuller test, the test statistics is less than the critical value. Therefore, the time series is not stationary. However, there are various methods to make a time series stationary.How to make a time series stationary?The assumption of stationarity is very important when modelling a time series, but most of the practical time series are not stationary. Eventually, we cannot make a time series one hundred percent stationary, most of the time, it will be with a confidence of 99%.Before going into detail, we will discuss on the reasons why the time series is not stationary. There are two major reasons to that, trend and seasonality.Having discuss the reasons, we will now talk about the techniques to make the time series stationary:TransformationLog transformation is probably the most commonly used form of transformation. Differencing Differencing is a widely used method to make the time series stationary. It is performed by subtracting the previous observation from the current one. When making the forecast, the process of differencing must be inverted to convert the data back to its original scale. This can be done by adding the difference value to the previous value.Using the Dickey-Fuller test we can see that the test statistic is -2.717131 and that the critical values at 1%, 5% and 10% are -3.482501, -2.884398 and -2.578960 respectivelyThe time series is stationary with 90% confidence. The second or third order differencing can be done to get better results. Decomposition In decomposition, the time series is divided into several components mainly trend, cyclical, seasonal and irregular components.The time series can sometimes be broken down into an additive or multiplicative model.We will assume a multiplicative model for our example.Since the trend and seasonality were separated from the residuals, we can check the stationarity of the residuals.Results of Dickey-Fuller Test is test statistic is -6.332387e+00 and the critical values at 1%, 5% and 10% are -3.485122e+00, -2.885538e+00 and -2.579569e+00 respectively. We can conclude that the time series is stationary at 99% confidence.Now, we can go forward with the forecasting.Forecasting the time seriesWe will fit this time series using the ARIMA model, ARIMA is an acronym that stands for Autoregressive Integrated Moving Average. It is a linear equation similar to a linear regression. The first goal is to find the values of the predictors (p, d, q), but before finding these values, two situations in stationarity must be discussed. A strictly stationary series without any dependence among the values. In this case, we can model the residual as white noise.The second case is a series with significant dependency among the values.The predictors mainly depend on the parameters (p, d, q) of the ARIMA model:Number of AR(Auto-Regressive) terms (p)It is the number of lag observation that were included in the model. This term helps to incorporate the effect of the past values into the model. Number of MA (Moving Average) terms (q)It is the size of the moving average window, that is, this term sets the error of the model as a linear combination of the error values observed at previous time points in the past.Number of differences(d)The number of times that the raw observations are differenced.In order to obtain the values of p and q, we will use the following two plots:Autocorrelation Function, ACFThis function will measure the correlation of the time series with its lagged version. Partial Autocorrelation Function, PACFThis function measures the correlation between the time series with a lagged version of itself, controlling the values of the time series at all shorter lagsIn the ACF and PACF plots, the dotted lines are the confidence interval, these values are p and q. The value of p is obtained from the PACF plot and the value of q is obtained from the ACF plot. We can see that both p and q are 2.Now, that we have obtained p and q, we will make three different ARIMA model: AR, MA and the combined model. The RSS of each of the model will be given.AR modelMA modelCombined modelFrom the plots, it is clearly shown that the RSS of AR and MA are the same and that of the combined is much better. As the combined model give a better result, the following steps will take the values back to its original scale.The predicted results are stored.The differencing is converted the log scale. This can be done by adding the differences consecutively to the base numbers.The exponent is taken and is compared to the original scale.Therefore, we have the final result. References Aarshay Jain(2016) A comprehensive beginner’s guide to create a Time Series Forecast (with Codes in Python) [WWW] Available from https://www.analyticsvidhya.com/blog/2016/02/time-series-forecasting-codes-python/ [Accessed 14/04/18] Maxime Phillot (2017) How do I interpret the results in an augmented Dickey-Fuller test? [WWW] Available from https://www.quora.com/How-do-I-interpret-the-results-in-an-augmented-Dickey-Fuller-test [Accessed 23/04/18] Jason Brownlee (2016) What Is Time Series Forecasting? [WWW] Available from https://machinelearningmastery.com/time-series-forecasting/ [Accessed 23/04/18] Chris St.Jeor and Sean Ankenbruck (2018) Time Series for dummies- The 3 step process [WWW] Available from https://www.kdnuggets.com/2018/03/time-series-dummies-3-step-process.html [Accessed 22/04/18] Pennsylvania state university (n. d) Overview of Time Series Characteristics [WWW] Available from https://onlinecourses.science.psu.edu/stat510/node/47 [Accessed 22/04/18] How to cite Time Series, Papers Time Series Free Essays Introduction A time series is a set of observations, xi each one being recorded at a specific time t. After being recorded, these data are rigorously studied to develop a model. This model will then be used to construct future values, in other words, to make a forecast. We will write a custom essay sample on Time Series or any similar topic only for you Order Now When looking at a time series, some questions must be asked:Does the time series have a trend or seasonality?Are their outliers? Is there constant variance over time?Essential of Good time seriesThe data must be long enough.There must be equal time gap.There must be a normal period.Example1The following plot is a time series plot of the annual number of earthquakes in the world with seismic magnitude over 7.0, for 99 consecutive years. By a time series plot, we simply mean that the variable is plotted against time.Some features of the plot:There is no trend.The mean of the series is 20.2.There is no seasonality as the data are annual data.There are no outliers.Example 2 This shows a time series of quarterly production of beer in Australia for 18 years.Some features are:There is an increasing trend. There is seasonality.There are no outliers.The Components of Time SeriesThe components of time series are factors that can bring changes to the time series:Trend component, TtWhen there is an increase or a decrease over a long period of time in the data, then we say that there is a trend. Sometimes, a trend is said to be changing direction when it goes from an increasing trend to a decreasing one. It is the result of events such as price inflation, population growth or economic changes. Seasonal component, StA seasonal pattern exists when the time series exhibits regular variations at specific time. It arises from influences such as natural conditions or social and cultural behaviors. For example, the sales of ice-cream are relatively high in summer. So, the salesman expects greater profit in summer than in winter. Cyclic component, CtIf the time series shows an up and down movement around a given period of time, it is said to have a cyclical pattern.Irregular component, ItIrregular components consist of changes that are unlikely to be repeated in a time series. Examples are floods, fires, earthquakes or cyclones.Combining the time series componentsTime series is a combination of the components which were discussed above. These components can be either combined additively or multiplicatively.Additive modelIt is linear, and the changes are made by the same amount over time.Yt = Tt + Ct + St + ItMultiplicative modelIt is non-linear such as quadratic or exponential, and the changes increase or decrease over time.Yt = Tt Ãâ€"Ct Ãâ€" St Ãâ€" ItUsesTime series can be useful in the following fields: StatisticsSignal processingEconometricsMathematical financeAstronomyEarthquake predictionsWeather forecastingImportance of Time series for businessesThere are many benefits of time series for business purposes:Helpful for study of past behaviorBusinessmen use time series to study the past behaviors and to see the trend of the sales or profit of their businesses. Helpful in forecastingTime series is a great tool for forecasting. Businesses can make a time series of the past strategies of their competitors and make an estimate of their future strategies. In this way, they make can built a better strategy and make more profits.Helpful in comparisonTime series can be used to calculate the trend of two or more branches of the same company and compare their performance. On their performances, rewards can be given. However, time series can have some limitations for a business. Sales forecasting relies on the past results to predict future expectations. But, if a company is new, there is a limited amount of data to make predictions. Even so, past results do not always indicate what the future sales will be.To fully understand this topic, we will work out this example. Example 2We will consider the actual arrival of passengers from an airport over the year 1949 to 1960. From these data, we will make a forecast.The first step is to plot the data and obtain descriptive measures such as trends or seasonal fluctuations.The second step is to check for the stationarity of the time series.StationarityA time series is said to be stationary if its mean and variance does not change over time. Obviously, not all the time series that we encounter are stationary. It is important because, most of the models we work on, assumes that the time series is stationary. If the time series has the same behavior over time, there will be a high probability that it will follow the same trend in the future.How to check for stationarity?For the graph that was plotted, we can see that it has an increasing trend with some seasonal pattern. But, it is not always evident to see whether a plot is increasing or has a seasonal trend. We can check for stationarity using the following:Plotting rolling statisticsWe plot the moving average or variance and see whether it changes with time. But, as it is a visual technique, we will take more consideration for the next test. Dickey-Fuller testIt is one of the statistical methods to check for stationarity. The null hypothesis is that the time series is non-stationary, and the alternative hypothesis is the converse.As shown below, the test consists of the test statistics and critical values at different significant levels. If the test statistics is less than the critical value, we reject the null hypothesis. Results of Dickey-Fuller Test: Test Statistic 0.815369p-value 0.991880#Lags Used 13.000000Number of Observations Used 130.000000Critical Value (1%) -3.481682Critical Value (5%) -2.884042Critical Value (10%) -2.578770According to the Dickey-Fuller test, the test statistics is less than the critical value. Therefore, the time series is not stationary. However, there are various methods to make a time series stationary.How to make a time series stationary?The assumption of stationarity is very important when modelling a time series, but most of the practical time series are not stationary. Eventually, we cannot make a time series one hundred percent stationary, most of the time, it will be with a confidence of 99%.Before going into detail, we will discuss on the reasons why the time series is not stationary. There are two major reasons to that, trend and seasonality.Having discuss the reasons, we will now talk about the techniques to make the time series stationary:TransformationLog transformation is probably the most commonly used form of transformation. DifferencingDifferencing is a widely used method to make the time series stationary. It is performed by subtracting the previous observation from the current one. When making the forecast, the process of differencing must be inverted to convert the data back to its original scale. This can be done by adding the difference value to the previous value. Using the Dickey-Fuller test we can see that the test statistic is -2.717131 and that the critical values at 1%, 5% and 10% are -3.482501, -2.884398 and -2.578960 respectivelyThe time series is stationary with 90% confidence. The second or third order differencing can be done to get better results.DecompositionIn decomposition, the time series is divided into several components mainly trend, cyclical, seasonal and irregular components. The time series can sometimes be broken down into an additive or multiplicative model.We will assume a multiplicative model for our example.Since the trend and seasonality were separated from the residuals, we can check the stationarity of the residuals.Results of Dickey-Fuller Test is test statistic is -6.332387e+00 and the critical values at 1%, 5% and 10% are -3.485122e+00, -2.885538e+00 and -2.579569e+00 respectively. We can conclude that the time series is stationary at 99% confidence.Now, we can go forward with the forecasting.Forecasting the time seriesWe will fit this time series using the ARIMA model, ARIMA is an acronym that stands for Autoregressive Integrated Moving Average. It is a linear equation similar to a linear regression. The first goal is to find the values of the predictors (p, d, q), but before finding these values, two situations in stationarity must be discussed.A strictly stationary series without any dependence among the values. In this case, we can model the residual as white noise.The second case is a series with significant dependency among the values. The predictors mainly depend on the parameters (p, d, q) of the ARIMA model:Number of AR(Auto-Regressive) terms (p)It is the number of lag observation that were included in the model. This term helps to incorporate the effect of the past values into the model.Number of MA (Moving Average) terms (q)It is the size of the moving average window, that is, this term sets the error of the model as a linear combination of the error values observed at previous time points in the past. Number of differences(d)The number of times that the raw observations are differenced.In order to obtain the values of p and q, we will use the following two plots:Autocorrelation Function, ACFThis function will measure the correlation of the time series with its lagged version. Partial Autocorrelation Function, PACFThis function measures the correlation between the time series with a lagged version of itself, controlling the values of the time series at all shorter lagsIn the ACF and PACF plots, the dotted lines are the confidence interval, these values are p and q. The value of p is obtained from the PACF plot and the value of q is obtained from the ACF plot. We can see that both p and q are 2. Now, that we have obtained p and q, we will make three different ARIMA model: AR, MA and the combined model. The RSS of each of the model will be given.AR modelMA modelCombined modelFrom the plots, it is clearly shown that the RSS of AR and MA are the same and that of the combined is much better. As the combined model give a better result, the following steps will take the values back to its original scale. The predicted results are stored.The differencing is converted the log scale. This can be done by adding the differences consecutively to the base numbers.The exponent is taken and is compared to the original scale.Therefore, we have the final result. References Aarshay Jain(2016) A comprehensive beginner’s guide to create a Time Series Forecast (with Codes in Python) [WWW] Available from https://www.analyticsvidhya.com/blog/2016/02/time-series-forecasting-codes-python/ [Accessed 14/04/18]Maxime Phillot (2017) How do I interpret the results in an augmented Dickey-Fuller test? [WWW] Available from https://www.quora.com/How-do-I-interpret-the-results-in-an-augmented-Dickey-Fuller-test [Accessed 23/04/18]Jason Brownlee (2016) What Is Time Series Forecasting? [WWW] Available from https://machinelearningmastery.com/time-series-forecasting/ [Accessed 23/04/18]Chris St.Jeor and Sean Ankenbruck (2018) Time Series for dummies- The 3 step process [WWW] Available from https://www.kdnuggets.com/2018/03/time-series-dummies-3-step-process.html [Accessed 22/04/18] Pennsylvania state university (n. d) Overview of Time Series Characteristics [WWW] Available from https://onlinecourses.science.psu.edu/stat510/node/47 [Accessed 22/04/18] How to cite Time Series, Papers

Trade Union and Labour Relation

Questions: Part 1 Read the case of Medivance Instruments Ltd v Gaslane Pipework Services Ltd and another [2002] All ER (D) 111 (Apr) and using this case only answer the questions below. 1. What judges heard this case in the Court of Appeal? 2. Who was the appellant and who were the two respondents in the Court of Appeal? 3. What is the difference between the test of merchantable quality Sale of Goods Act and the test of fitness for purpose in? 4. Did s.14 of the Sale of Goods Act apply to Vulcana? Give reasons for your answer. 5. Why did Neuberger J limit the appeal to the issues around s.14 and the tortious equivalent? 6. According to the appellant, why was the heater not of merchantable quality and/or fit for purpose? 7. What effect would it have on business if a claim under s.14 was won every time it was shown that the product in question could have been made safer? 8. Did the judges believe that a different heater should have been supplied to the appellant? Give reasons for your answer. 9. Why did Neuberger J rely on the case of Wright v Dunlop (1973) 7 KIR 255? 10. According to Mr Brown, why might it be dangerous to always allow a seller to avoid liability through warning the buyer of the defect? (2 marks) 11. Why did Neuberger J refer to the cases of Holmes v Ashford and Hodge Sons v Anglo American Oil Co.? 12. Which of the following were material facts in the case? a. If the appellant had known that there were heaters with thermostat devices included, he would have bought one. b. The appellant had told the respondents that the heater would be used in a packing area. c. There were a mixture of heaters on the market including those that contained a thermostat and those that did not. d. Vulcana's brochure described the heater as having an "overheat switch [which is] fail safe on overheating" and "Full safety protection provided electronically". e. The heater complied with the British Standard and had been certified by British Gas. f. The instructions for the heater contained a clear warning that it should be left unobstructed. This warning was brought to the attention of the appellant. 13. Which of the following was the ratio decidendi of the case? If you think a statement is part of the ratio decidendi explain why. If you think a statement is not part of the ratio decidendi explain why. a. It would be inappropriate for a court to impose, through the medium of tort or of implied contractual terms, any obligation on a seller which involves a higher duty than that which the parties have expressly imposed in their contract, or which the legislature has imposed through section 14. b. The heater was of merchantable quality and fit for the purpose for which it was supplied. c. Where a commercial buyer has previous experience buying a similar product and is aware of the risks in using that product, then the product is likely to be fit for purpose under section 14. d. If it can be shown that a desirable improvement to the article was common practice, easy and cheap to achieve, and had obvious benefits, then a buyer's prospect of establishing lack of merchantable quality or of suitability for purpose obviously would be enhanced. e. The fire was caused by a blockage on the front grill of the heater which resulted in the temperature rising to such a level that the containers ignited. 14. Mr Matthews owns a shoe shop. The shoe shop has a shop floor and a small, narrow, stock room which contains hundreds of cardboard boxes. The cardboard boxes contain shoes. Mr Matthews wished to purchase a heater for the stock room to use during winter so that his two stock room staff would be kept warm. Mr Matthews asked JTL, a heating company, to visit the store room and recommend a heater to purchase. The JTL representative recommended their standard heater which did not include a safety guard or thermostat. JTL installed the heater and explained to Mr Matthews that nothing should be placed within a metre radius of the heater. Mr Matthews signed a document confirming that he understood this. A few weeks later, Mr Matthews left an empty cardboard shoe box directly in front of the heater and within an hour the stockroom had caught fire. Mr Matthews is now claiming that the heater was not of merchantable quality and not fit for purpose. He had never purchased a heater before and had trusted JTL. JTL believes that the heater conformed to British Safety Standards and they adequately warned Mr Matthews not to put anything within a metre radius of the heater. Using only the case of Medivance Instruments Ltd v Gaslane Pipework Services Ltd and another, advise JTL on these claims. (15 marks) Part 2 Read the Trade Union and Labour Relations (Consolidation) Act 1992 (the Act) and using this statute only answer the following questions. 1. What is the short title of the Act? 2. What is the long title of the Act? 3. On what date did the Act come into force? 4. What linguistic presumption would the courts use to determine whether something is included in s.137(5)? Give reasons for your answer. 5. How would courts determine what advertisement means in s.137(3)? 6. Sophie is looking for a job as a teacher. She has recently applied for a teaching position at Hansroad Secondary School. The Head Teacher of this school is a strong believer in supporting a national teaching trade union called Teach Excel Union. This union helps to compile a short-list for interviews held at the school. The union is aware that Sophie is not a member of any trade union and refuses to offer her an interview for this position. Advise Sophie. 7. Marlon is a builder. He attended an interview to become a full-time builder at a construction company called Zeon Limited. In the interview the manager, Henry, asked Marlon whether he was a member of any builderstrade unions. Marlon replied that he was not a member. Henry told Marlon that he would be offered the job if he did not become a member of a trade union. Marlon felt uncomfortable with this request and explained that he could not guarantee that he would never become a trade union member. Henry refused to offer the job to Marlon. Marlon experienced severe stress and anxiety after this refusal and he was unable to work for one month. Advise Marlon. 8. IT World Ltd is an IT retailer that sells computers. Most staff members are members of an IT trade union. IT World Ltd started a redundancy process and proposes to dismiss 150 employees. IT World Ltd started consulting 35 days before it dismissed an employee for redundancy reasons. As part of the consultation, IT World Ltd consulted with senior staff members. One of these senior staff members is a trade union representative. There are five trade union representatives in total at IT World Ltd. IT World Ltd orally told the senior staff members how many people would be made redundant and the reasons for the redundancy. They also asked some other staff members how IT World Ltd could reduce the number of employees to be dismissed. However, when one staff member made a suggestion, IT World Ltd refused to listen. Advise IT World Ltd on their liability under the Act. 9. A catering company has suggested that they need to dismiss 25 employees. Under what rule of statutory interpretation would the company be required to start a consultation under s.188(1) and why? 10. Marketing Solutions accountant, Simon, is a member of an independent trade union which is recognised by Marketing Solutions. Simon has requested time off to represent the union at a trade union conference. Marketing Solutions has told Simon that as it is near the end of the financial year, they need him to work. They have denied Simons request to attend the conference. Advise Simon. Answers: 1. The names of the Judges who heard the appeal are as follows: Lord Justice Thorpe Lord Justice Mance Mr Justice Neuberger 1. Medivance Instruments Ltd was the appellant in the matter. Gaslane Pipework Services Ltd and Vulcana Gas Appliances Limited are the two defendants of the case. 2. There is basic distinction between Section 14(2) and Section 14(3) of the Sales of Good Act 1979. Section 14(2) of Act, applies an implied term that the goods supplied shall be of good quality. Section 14(3) of the Act, states that the goods supplied shall be of the quality for which it has been purchased. The difference lies in the fact that one speaks of the quality of the product in ordinary sense and another speaks of the purpose for which the product has been bought. 3. In my opinion Vulcana is responsible under Section 14 of the Sales of Good Act, because as the manufacturer of the heater, it should have taken care of the fact, that it has mechantable quality and is fit for the purpose for which it has been purchased in the due coarse of the business. In that way Vulcana was negligent in fulfilling both the implied conditions. 4. Justice Neuberger was of the view that the appellant was well aware of the fact as to what to be used and what not. The thing used by the appellant was not permitted by the supplier and as such the appellant was well aware of the risk or incident that has taken place in the due course of using the restricted thing. Hence on the above ground, J Neuberger limited the scope of appeal involving Section 14. 5. According to petitioner the heater supplied was not of standard quality nor was it suitable to serve the purpose. The appellant was of the opinion that there was no thermostat that would have prevented from happening of the event. Moreover, no pan was taken by the defendant for installation of such device. 6. If every company would bring up an issue under Section 14, seeking that the goods supplied are of not merchantable quality or is not suitable for the purpose, then the manufacturer companies would run at a loss and they would have to keep compensating for no reason . Section 14 shall be critically judges so as to save the manufacturers from any unfair decision for the fact that if it becomes an easy practice for the buyers then would be broadly enhanced. 7. The judges were of the opinion that the heater would have no doubt could have been more safer, but it doesnt make the change the fact that the product supplied was not of standard quality as per required by law nor was it suitable for purpose . The reason for stating such a comment is that firstly Section 14 doesnt requires to impose high grade quality of goods as a consequence of ordinary language. Secondly, they were of the opinion if desirable improvement to the article was a common practice, then the buyers prospect would have definitely enhanced . Thirdly, if they buyer had already known the fact that other heaters in the market was being served with thermostat, then they would have bought it from some other place or would have mentioned there requirement while placing the order. 8. The point on which the judges relied on the case of Wright v Dunlop, is the duty of reasonable care. The judges were of the opinion that if a manufacture discovers that the product is unsafe in any manner, then it is his duty to cease the delivery of such a product or if that cannot be done, then atleast it should inform the buyer about the relevant facts and the risk linked with it. This is known as the reasonable duty of care borne by the supplier to the buyer . 9. According to Mr Brown, if a seller is often permitted to neglect his liability for a defect, just by giving an intimation about any defect, then it is to be presumed that the seller is being allowed to define the extent of his duty in regards to a contract, regardless of the situation. 10. Both the case of Homes v Ashford and Hodge Sons v Anglo American Oil Co, dealt with one point that is negligence. It was selected on that ground by the judges. 11. Material Facts: If the appellant had known that there were heaters with thermostat devices included, he would have bought one is a material fact of the case. It is a relevant fact of the case, that he petitioner had informed the respondents about the issue of placing the heater in the packing area. There were a variety of heaters available in the market of which some contained a thermostat and some did not is a material fact of the case. 12. Vulcana's brochure described the heater as having an "overheat switch [which is] fail safe on overheating" and "Full safety protection provided electronically" not a material fact in the case . The heater abided with the standard set forward by the British Standard and had been passed by British Gas is a material fact of the case. It was clearly instructed that the heater shall be left unhampered. This information was provided to the petitioner is a material fact of the case. 13. Ratio Decidendi of a case: It is definitely one of the ratio decidendi of the case. It would be definitely incorrect for the court to impose on the seller on the basis of tort or implied contractual term, the higher standard of duty under section 14 as Section 14 of the Act states that there should be a merchantable quality of the product in the ordinary sense. Ordinary sense doesnt include high standard within its scope . It is a ratio decidendi of the case that the product supplied was of merchantable quality and suitable for the purpose, as the heater supplied was confirmed by the British Standard to be safe and at the same time the appellant was well aware of it. The following point that where a buyer is already aware of the product as he has bought it before and also aware of the risk involved it, is likely to be fit for the purpose of Section 14 is not a ratio decidendi of the matter as previous purchase doesnt decide the quality of the future purchased product . It is to be set herein that it is a ratio decidendi for the case as it is quite a logical view in the eyes of law, that if every purchaser claims for a better quality, then most of the time goods will be returned and suppliers will be penalised, thereby causing loss to the suppliers in turn. It is not a ratio decidendi of the case as it has been noted that the appellant had left cardboards in front of the heater which he was not permitted to do. 14. ADVICE: No electric appliances that can cause hazard, are made available to the market for the buyers unless the product has passed the test of standard of production set by the British Standards Institution . The heater supplied by the JLT Company was confirmed by the British Standards and then only it was made available in the market for the buyers to avail it. Secondly, JLT Company as repeatedly informed Mattew about the safety guard or absence of thermostat in the heater and about the rick involving it. After warning Mattew, he was made to sign a document which stated that he was well aware of the facts of risk that are involved and he have been warned by JLT Company in that regards. Observing the above mentioned matter, JLT Company shall not be held liable under section 14 of the Sales of Good Act, since the goods supplied by them was at the first place confirmed by the British Standards and secondly they have warned about it to Mattew, which implies they have done reasonable duty of care towards the buyer as prescribed law . Hence in that respect, the JLT Company shall put forward the expert evidence of the British Standard and at the same time shall also produce the signed document as evidence stating that Mattew was well aware of the risk involved in the heater. PART II: Short Title of the Act is Trade Union and Labour Relations (Consolidation) Act, 1992. 1. An Act to consolidate the enactments relating to collective labour relations, that is to say, to trade unions, employers associations, industrial relations and industrial action. 2. The act came in force on 16th July, 1992. 3. Section 137(5) states that any person shall be presumed to have suffered refused employment, if he requires employment under a person and for a case that person deliberately omits or refuses to proceed with the process of his application or causes him to cease his application or intentionally avoids to offer him employment or offers that person such a form of employment that no employer of reasonable mind would offer or acceptable in nature or makes him an offer of employment but at the same time forces him to cease his application . 4. Advertisement means every form of advertisement or notice that invites employment offers to any person who might or might not be a part of any trade union and who might not satisfy the conditions provided in the advertisement for the employment for which he is subjected to refuse employment . 5. Sophie is looking for a job, but she has not been offered job for she is not found to be a part of any trade union . She is presumed to be taken refused employment under Section 137(5) (c) which states that she was deliberately not offered employment. She can file before the employment tribunal for her right to employment is being infringed for which she needs to be compensated . 6. Section 140 allows a claim to be lodged before the employment tribunal for a complaint under Section 137. Herein, Marlon was refused employment because he was given an unreasonable condition by the employer that he can never join a trade union, which is a complaint under section 137 (5) (d). He can lodge a complaint under Section 140 claiming for compensation for the loss suffered by him due to refused employment. The tribunal in its discretionary power can either order the respondent to pay a compensation amount or can advice to act in a way recommended within a prescribed period. 7. It is a well established rule under Section 188 of the Act, that where an employer wishes to dismiss as redundant 20 or more employees within a period of 90days or less, the employer will be under an obligation to suggest all the person who are appropriate representatives of the employees regarding the dismissal . If the organization wishes to dismiss 100 or more than 100 employees, then they are to consult representatives atleast 45days before the first dismissal . Herein in this matter the IT world Ltd took a decision to dismiss 150 employees and consulted only 35days prior to first dismissal. Secondly they rejected to hear the consultation of one of the representatives of the employees, which is mandatory under Section 188 (1). 8. It is required under Section 188 (1), that ifa company decides to dismiss 20 or more employees as redundant, then it need to consult with all the representatives of any of the employees 90 days prior to the first dismissal, which must be atleast 30days. 9. It has been held under Section 170 of the Act, that an employer is bound to allow an employee who is a part of trade union identified by the employer, time off through his working hours to take part in activities of union . Simon was not allowed time off by the marketing solutions. Simon can lodge a complaint against his employer under Section 170 (4) stating that his employer rejected to approve his requested time off. References Addison, J, 'The consequences of trade union power erosion'. inIZAWOL, , 2014. 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