The Transatlantic Trade and Investment Partnership
The Transatlantic trade and Investment partnership (TTIP) is a proposed agreement of free trade between the European Union and the United States of America. The aim of this agreement is to do away with the trade obstacles present in an extensive range of economic sectors (TELÒ, 2013). Removal of these barriers will make it easier to carry out trade between the European Union and the United States of America. Apart from cutting tariffs across all sectors, the United States of America and the European Union intend to deal with barriers such as the disparities in technical regulations, standards and procedures approval. Such barriers are responsible for unnecessary money and time costs incurred by companies who wish to sell their goods in both markets. For this proposal to be agreed upon there is a need for tests in the form of research to provide evidence on the effects of signing and implementation of the Transatlantic Trade and Investment Partnership (TTIP) in United Kingdom. Apart from carrying out of the two study tests, there are a number of other factors to be considered.
The proposed TTIP is meant to open up trade between United Kingdom and the United States of America. This makes trade openness a huge factor in ensuring successful trading between the two countries. However, apart from trade openness, there are other factors, which might affect the level of prices, output and employment. These factors can be determined by the use of aggregate demand-aggregate supply model. This macroeconomic model explains price level and output by the use of the relationship between aggregate demand and aggregate supply (GWARTNEY, 2009, pg.234). The main factors involved are; the long run aggregate supply, short run aggregate supply and aggregate demand. Aggregate demand is the main cause of changes in the economy; this is because, expansionary changes in the policy of the aggregate demand curve to the right while contractionary moves the aggregate demand curve to the left. Changes in aggregate demand lead to a price level change. Short-run aggregate supply shifts only as a response to the aggregate demand curve. In the case of a supply shock, however, the short-run aggregate supply curve shifts without any prompting from the aggregate demand curve. Positive supply shock causes the price level for a specified amount of output to reduce. In the long run, aggregate demand adjust to new prices and output levels. Therefore, a positive supply shock will result to an increase in the output levels and decrease in price levels in the short run but will only cause the level of the prices to reduce in the end (HALL & LIEBERMAN, 2013, pg.849).
The point where short run aggregate supply curve intersects with the long-run aggregate supply curve and the aggregate demand curve shows the equilibrium output level and the equilibrium price level.
Time series analysis are methods used in the analysis of time series data for extraction of meaningful statistics and other characteristics of the data (SAYED& LUGHOFER, 2012, pg.304). Before the signing of the proposed TTIP, a time series analysis of the data from the past in UK can be used to predict the future. The reliability of a time series analysis is sometimes put into question and mostly depends on the model or method used to carry out the analysis. To make sure this analysis provides reliable information, one, should use the latest version of Regression Analysis of Time Series (RATS) software. (RATS) software provides all the essentials, which include estimating, linear and non-linear least squares, and ARIMA models. (RATS) software supports systems such as ARCH, GMM and GARCH, vector auto regressions (VARs), state space models, ), spectral analysis, DSGEs, and much more. (RATS) can handle time series of nearly all frequencies which include both daily and weekly and creates graphs of publication-quality for printing or introducing straight into word processors. “Wizards” which are menu driven offer a point and click interface for many shared tasks, making (RATS) a perfect tool for fresh users and for educational situations. In the meantime, the authoritative command driven language at the core of the program remains easier to learn and usage for simple tasks, while letting users to automate multifaceted or repetitive chores and even write stylish menu and dialog-driven end-user applications. (RATS) software is accessible for Windows, Unix, Macintosh, with complete compatibility across platforms (MONTGOMERY, 2008). The latest version, (RATS 9) is more improved and capable of producing reliable information. Some of the improvements include revised and expanded manuals, multi-threaded execution for better performance, new editor with many new features, “Find in Files” operations which locates useful examples, More point-and-click Wizards, Many new built-in functions, Option to compute more accurate numerical derivatives, Estimates of completion time for long operations, HASH and LIST types for flexible handling of “vector” information and the ability to pass functions to procedure. This software is, therefore, capable of coming up with more reliable information.
Cross sectional analysis are aimed at determining the frequency of a particular attribute. In this type of study, subjects are contacted at a fixed point in time and pertinent info is gotten from them (BOWLING, 2005, pg.120). Because of this info, they are then categorized as having or not having the attributes of interest. Before the signing of the proposed TTIP, there is, need to study data from other countries so that this can give an insight on what might happen after the proposal has been agreed upon. To find out this, cross sectional analysis should be carried out. The reliability of this analysis is questionable and therefore one needs to carry out the analysis as indicated so that they can obtain reliable information. They should start by clearly defining the attribute of interest to avoid confusion and ensure the correct results are noted. Next, a suitable source population needs to be identified since the source population is generally more limited than the target population. This is then followed by choosing a representative sample from the source population. A smaller sample will give more accurate results than a large sample. To improve reliability of the analysis, a representative sample should be selected according to the sample design employed. The best design that improves reliability of the analysis is the random sampling method. Random sampling is more reliable since chance alone determines who will be included in the sample, removing any possibility of selection bias (CHANG, 2006, pg.127).
Most of the economic, literary works are of the view that trade openness causes a rise in well-being resulting from enhanced distribution of national resources. Import limitations of any type generate an anti-export prejudice by raising the cost of importable merchandises comparative to exportable goods (VELDE, 2006). The removal of this prejudice by trade openness will motivate a swing of resources from the making of import alternates to the making of goods meant for export. This leads to the generation of development from the short to medium term as the country adjusts to a fresh provision of resources additional in retention with its comparative advantage. This procedure is neither even nor involuntary. On the contrary, it is expected to make alteration prices, surrounding an extensive assortment of possibly detrimental short-term results. These results may comprise a decrease in employment and output, industry loss and human capital for various firms and macroeconomic unpredictability caused by problems in balancing of payments or reductions in government. The extent of the modification prices relies on the speed with which resources transition around various sectors. One factor that links to trade openness in influencing trade agreements on output, prices and employment is the aggregate demand. Aggregate demand is the summation of all the demands in a given economy at a given time (GLANVILLE& GLANVILLE, 2011, pg.209). There are varieties of effects in aggregate demand change, but the most notable ones are changes in the output and price. The increase in the overall aggregate demand will result to a right shift of the aggregate demand curve while a decrease in the aggregate demand results to a leftward shift of the aggregate demand curve. This implies that an increase of the inputs to aggregate demand will lead to a higher quantity of real output or increased price level. Combining trade openness with aggregate demand will lead to a balance in the economy since trade openness causes reduced outputs, employment and price level while an increase of the inputs to aggregate demands leads to increased output and price levels. Trade openness leads to increased specialization, tougher competition, and higher scales of production, larger
Products diversity and enhanced productivity. All these factors result into reduced aggregate demand, this way; trade openness is able to keep aggregate demand nearer to the equilibrium.
The proposed Transatlantic trade and Investment partnership (TTIP) between United Kingdom and United States of America is likely to bring various advantages and a couple of disadvantages with it if implemented. It is, therefore, very necessary to carry out various studies, which can help in the prediction of what might happen in the future of the United Kingdom’s economy. These studies will enable the key decision makers to be at a better position when it comes to making of the final decision.
References
BOWLING, A. (2005). Handbook of health research methods: investigation, measurement and analysis. Maidenhead, Open Univ. Press.
CHANG, A. E. (2006). Oncology an evidence-based approach. New York, Springer. http://public.eblib.com/choice/publicfullrecord.aspx?p=338400.
GLANVILLE, A., & GLANVILLE, J. (2011). Economics from a global perspective: a text book for use with the IB diploma economics programme. Dolton, Glanville Books.
GWARTNEY, J. D. (2009). Macroeconomics: private and public choice. Mason, OH, South-Western Cengage Learning.
HALL, R. E., & LIEBERMAN, M. (2013). Economics: principles & applications. Australia, South-Western Cengage Learning.
MONTGOMERY, D. C. (2008). Introduction to statistical quality control. Hoboken, N.J., Wiley.
SAYED-MOUCHAWEH, M., & LUGHOFER, E. (2012). Learning in non-stationary environments: methods and applications. New York, NY, Springer.
TELÒ, M. (2013). Globalisation, multilateralism, Europe: towards a better global governance? Farnham, Ashgate.
VELDE, D. W. T. (2006). Regional integration and poverty. Aldershot [u.a.], Ashgate.
