Econometrics report factors affecting the demand for red meat in european countries

FOREIGN TRADE UNIVERSITY FACULTY OF INTERNATIONAL ECONOMICS *** ECONOMETRICS REPORT FACTORS AFFECTING THE DEMAND FOR RED MEAT IN EUROPEAN COUNTRIES Name: Group Class: KTEE218.1 Instructor: MS Nguyen Thuy Quynh Hanoi, September 2021 ECONOMETRICS REPORT KTEE218.1 GROUP INDIVIDUAL ASSESSMENT Nguyễn Quỳnh Anh Nguyễn Thanh Hằng Nguyễn Vân Thùy Linh Phạm Khánh Linh - 10 10 10 Nguyễn Thanh Hằng 10 - 10 10 Nguyễn Vân Thùy Linh 10 10 - 10 Phạm Khánh Linh 10 10 10 - Average score 10 10 10 10 Evaluator Nguyễn Quỳnh Anh Page ECONOMETRICS REPORT KTEE218.1 GROUP DECLARATION The research “Factors affecting the demand for red meat in European countries” was carried out by Group 4, consisting of members Nguyen Quynh Anh, Nguyen Thanh Hang, Pham Khanh Linh and Nguyen Van Thuy Linh We hereby declare that we have collected the data and conducted the research ourselves We not use any outside help and support or use information not mentioned at the References of this Research Hanoi, 29/09/2021 Page ECONOMETRICS REPORT KTEE218.1 GROUP ACKNOWLEDGEMENTS Our group sincerely appreciates all the lectures that Prof Nguyen Thuy Quynh gave us! During the course time and the period we created this essay, you provided us with a wide range of valuable and interesting knowledge along with a lot of support and dedication whenever we had difficulties in studying Econometrics1 For us, it is our honor and lucky to have a wonderful teacher like you We put all our efforts on completing this essay as results of what we gained after the course Our essay may have shortcomings but we really hope that you will enjoy this essay and give us suggestions and comments so that we can be better for the next time If we have a chance, we hope that you will accompany us in many subjects in the future Thank you so much for everything you taught us! We will keep these knowledges in mind as long as possible Have a great day and stay healthy our dear teacher! Group Page ECONOMETRICS REPORT KTEE218.1 GROUP SUMMARY Topic: FACTORS AFFECTING THE DEMAND FOR RED MEAT IN EUROPEAN COUNTRIES Students - ID: Nguyễn Quỳnh Anh - 2013450004 Nguyễn Thanh Hằng - 2013450016 Nguyễn Vân Thùy Linh - 2013450029 Phạm Khánh Linh - 2013450032 Class: KTEE218.1 Instructor: MS Nguyễn Thúy Quỳnh Faculty: International Economics Keyword: red meat, demand, factors, Europe Our essay has the title: “Factors affecting the demand for red meat in European countries” This essay investigated the demand for meat in 41 countries in Europe in 2017 using the econometrics method The objective of our essay is to demonstrate the accuracy of Demand Function in Microeconomics and to estimate the change in demand for red meat through the relationship between demand and other factors such as price of red meat, price of substitution, chicken meat, population and income in the European market We collected data from valid sources like WORLDBANK, NUMBEO and FAOSTAT The data were analysed using the ordinary least square method and multiple regression analysis Results show strong agreement with theoretical predictions, which is that the demand for red meat is influenced by price of substitutes, the number of people in each country, and income per head of consumers positively The results of hypothesis testing reveal a reverse relationship between demand for red meat and its price, according to the Demand Function The work presented here recommends that the government should implement policies to increase income per capita to augment demand for red meat Page ECONOMETRICS REPORT KTEE218.1 GROUP TABLE OF CONTENT INTRODUCTION SECTION OVERVIEW OF THE TOPIC 1.1 Definition and Theory of Demand 1.1.1 Demand 1.1.1.1 Quantity demanded 1.1.1.2 Market demand and individual demand 1.1.2 Factors affecting quantity demanded 1.1.2.1 The law of demand (The relationship between quantity demanded of a good and its price) 1.1.2.2 Income of consumers 10 1.1.2.3 Prices of related goods 10 1.1.2.4 Number of consumers 11 1.1.2.5 Demand Function 11 1.2 Overview of the demand for red meat 11 1.3 Related published researches 11 1.4 Research hypothesis 14 SECTION MODEL SPECIFICATION AND DATA 15 2.1 Methodology 15 2.1.1 Method used to derive the model 15 2.1.2 Method used to collect and analyze the data 15 2.2 Theoretical model specification 15 2.2.1 Proxy to measure 15 2.2.2 Specify the model 17 2.2.3 Theoretical relationship between dependent variable and independent variables 17 2.3 Data description 18 2.3.1 Sources of data 18 Page ECONOMETRICS REPORT KTEE218.1 GROUP 2.3.2 Descriptive statistics and interpretation for each variable 18 2.3.2.1 Demand of red meat 19 2.3.2.2 Price of red meat 19 2.3.2.3 Price of chicken 19 2.3.2.4 Income of consumers 19 2.3.2.5 Number of consumers 19 2.3.3 Correlation matrix between variables 20 SECTION ESTIMATED MODEL AND STATISTICAL INFERENCES 22 3.1 Estimated model 22 3.2 Statistical inferences 24 3.2.1 Hypothesis testing 24 3.2.1.1 Statistical significance of individual coefficients 24 3.2.1.2 Overall significance of the multiple regression 26 3.2.1.3 Joint significance of the price of red meat and the price of chicken 26 3.2.2 Consistency of the regression results with the theories 27 3.2.2.1 Consistency of the regression result with the theories 27 3.2.2.2 Mechanism of the relationships between variables 27 3.3 Recommendation and conclusion 28 3.3.1 Recommendation 28 3.3.2 Conclusion 29 REFERENCES 30 APPENDIX 31 Page ECONOMETRICS REPORT KTEE218.1 GROUP INTRODUCTION Red meat is a type of meat that has a bright red color and changes to darker color after cooking such as beef, pork, lamb, etc Red meat is known as one of the most popular cooking ingredients in the World It contains many nutrients such as iron, zinc, vitamin B12 and especially high protein, providing energy for human activities Red meat can also be easily made into dishes, from the casual to the high-end and brings delicious taste to people Therefore, it becomes one of the most consumed cooking ingredients in the World Europe is known as one of the areas with the largest consumption demand of red meat in the World However, the demand for red meat in this area cannot be completely free; it is still affected and limited by factors such as price, related commodity prices, income, number of buyers, etc In order to have an accurate view of the red meat consumption demand in Europe, we have conducted a research called “Factors affecting the demand for red meat in European countries” Our research objective is to describe the factors affecting the demand for red meat and to show the relationship and influence level of each of these factors to the quantity demanded of red meat in European countries The objects of our research are the demand for red meat in European countries and main factors affecting this, which are: prices, prices of related goods (chicken), people's income and number of consumers Our research scope includes parts: content scope, time scope and spatial scope The content scope is researching on factors affecting the demand for red meat in European countries The time scope of the data in this research is in 2017 The spatial scope includes 42 European countries This research consists of main sections In section 1, we present parts: the definition of all research objects mentioned in the research, the economic theories related to the research, other related researches and the research hypothesis In section 2, we mention parts: the methodology to derive the model and analyze the data, the theoretical model specification and describing the data In the last section, we show the estimation of the model, the hypothesis testing and recommendations Page ECONOMETRICS REPORT SECTION KTEE218.1 GROUP OVERVIEW OF THE TOPIC 1.1 Definition and Theory of Demand 1.1.1 Demand According to Robert S Pindyck & Naniel L Rubinfeld (1999), “The demand for a good or service is the quantity of that good or service that consumers are willing to buy in proportion to different prices over a specified period of time” 1.1.1.1 Quantity demanded The quantity demanded of any good is the amount of the good that buyers are willing and able to purchase (N.G Mankiw, 67) 1.1.1.2 Market demand and individual demand The quantity demanded in a market is the sum of the quantity demanded by all the buyers at each price Thus, the market demand curve is found by adding horizontally the individual demand curve (N.G Mankiw, 69) Also according to Pindyck, “the market demand curve is the horizontal summation of the demands of each consumer” (R.S Pindick, 122) The individual demand curve is a straight line, but the market demand curve can be kinked because the individual's willingness to buy prices may be different Based on Pindyck's analysis of individual and market demand (R.S Pindyck, 124), we can conclude that the factors that influence the demand of many buyers will influence the demand of the market 1.1.2 Factors affecting quantity demanded 1.1.2.1 The law of demand (The relationship between quantity demanded of a good and its price) “Other things being equal, when the price of a good rises, the quantity demanded of the good falls, and when the price falls, the quantity demanded rises” (N.G Mankiw, 67) Demand Curve: The demand curve shows how much of a good consumer is willing to buy as the price per unit changes (R.S Pindyck, 23) The demand curve is placed on a coordinate axis, the vertical axis represents price and the horizontal axis represents quantity The demand curve is a downward sloping line that shows the inverse relationship between price and quantity Page ECONOMETRICS REPORT KTEE218.1 GROUP In the law of demand, to simplify things, it is often assumed that factors such as consumer income, prices of related goods, consumer preferences, are constant factors However, in reality, these factors not always stand still, they change and affect the demand for a good In the following we examine the relationship between other factors and the demand for a good 1.1.2.2 Income of consumers According to N.G Mankiw theory, if a person's income decreases, they will be forced to spend less money on most goods, so their ability to buy is lower and that is the reason why their demand for goods reduces Similarly, if their income increases, their demand for goods also increases So, we say that the relationship between income and demand for goods is positive However, all quantitíes of goods and income not have a positive relationship If an increase in income leads to an increase in demand for a good, the good is normal good But, if an increase in income leads to an increase in demand for a good, the goods are inferior goods Attitude toward any goods depends on the income of the buyer, not on the quality of the goods 1.1.2.3 Prices of related goods There are two types of related goods: substitute goods and complementary goods (N.G Mankiw, 70) With two goods considered as substitutes, an increase in the price of one leads to an increase in the demand for the other Therefore, the relationship between the price of one good and the demand for the other is positive Page 10 ECONOMETRICS REPORT KTEE218.1 GROUP The below table is a conclusion for the descriptive statistics of our sample data: Variable Observations Mean Min Max 1381.233 Standard Deviation 2253.367 Quantity demanded of red meat Price of red meat Price of chicken Population Income 41 30.88196 11032.33 41 13.45415 8.740088 5.81 53.2 41 5.157561 1.892889 3.16 12.15 41 41 20.12111 5.175428 30.70433 8.3579 0.3434 0.0485663 144.4967 36.73506 2.3.3 Correlation matrix between variables The table as following is the correlation matrix between the variables that we use in the model: Variable Quantity demanded Quantity demanded Quantity demanded Quantity demanded Price of red meat Price of red meat Price of red meat Price of chicken Price of chicken Population Variable Price of red meat Price of chicken Income Population Price of chicken Population Income Population Income Income Correlation between variables -0.0929 -0.2672 0.7958 0.9671 0.5406 -0.1159 0.1361 -0.3126 -0.2072 0.7641 Based on the above results, we can see that the dependent variable, red meat quantity demanded, has a strong positive relationship with income and number of consumers (population) as the correlations are closer to Meanwhile, the correlations of the price of red meat and chicken towards income and population are just about below 0,3, showing that there is a loosely relationship between those On the contrary, income and number of consumers are closely linearly related as their correlation reaches 0.76 The table indicates that there is no perfect multicollinearity among our regressors, that is the correlation between two variables different from ±1 Thus, our sample Page 20 ECONOMETRICS REPORT KTEE218.1 GROUP data satisfy the assumption that there is no perfect multicollinearity of the GaussMarkov Classical Linear Regression Model assumptions Page 21 ECONOMETRICS REPORT SECTION KTEE218.1 GROUP ESTIMATED MODEL AND STATISTICAL INFERENCES 3.1 Estimated model We construct a 4-variable regression model based on the aforementioned economic theory to study impact of price of red meat, price of chicken, income of consumers and number of consumers on quantity demanded of red meat by running a regression with quantity demanded of red meat as a dependent variable and the other as independent variables, generated by STATA: ̂0 −312.3106 𝛽 ̂0 ) 289.9338 𝑠𝑒(𝛽 ̂1 Price of red meat −12.08532 𝛽 𝑡𝑠 −0.93 ̂1 ) 12.9452 𝑠𝑒(𝛽 ̂ Price of chicken 71.06222 𝛽2 𝑡𝑠 1.21 ̂2 ) 58.613 𝑠𝑒(𝛽 ̂3 Income 42.41617 𝛽 𝑡𝑠 2.40 ̂3 ) 17.6377 𝑠𝑒(𝛽 ̂4 Population 63.12332 𝛽 𝑡𝑠 13.36 ̂4 ) 4.72514 𝑠𝑒(𝛽 Residual sum of squares (RSS) 11085607.3 Explained sum of squares (ESS) 192020954 Total sum of squares (TSS) 203106561 The coefficient of determination (R ) 0.9545 The adjusted coefficient of determination (adjusted R ) 0.9394 Standard deviation of residual (𝜎̂) 554.92 Sample regression model: ̂0 + 𝛽 ̂1 𝑃𝑟𝑖𝑐𝑒𝑖 + 𝛽 ̂2 𝐶ℎ𝑖𝑐𝑘𝑒𝑛𝑖 + 𝛽 ̂3 𝐼𝑛𝑐𝑜𝑚𝑒𝑖 + 𝛽 ̂4 𝑃𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛𝑖 + 𝑢̂𝑖 𝐷𝑒𝑚𝑎𝑛𝑑𝑖 = 𝛽 Estimated model: Page 22 ECONOMETRICS REPORT KTEE218.1 GROUP 𝐷𝑒𝑚𝑎𝑛𝑑𝑖 = −312.3106 − 12.08532𝑃𝑟𝑖𝑐𝑒𝑖 + 71.06222𝐶ℎ𝑖𝑐𝑘𝑒𝑛𝑖 + 42.41617 𝐼𝑛𝑐𝑜𝑚𝑒𝑖 + 63.12332𝑃𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛𝑖 + 𝑢̂𝑖 ̂1 = −12.08532 infers that when the price of red meat The estimated coefficient 𝛽 increases by 1$ per kilogram, its quantity demanded is expected to decrease by 12.08532 billion kilograms, holding other variables constant Similarly, the increases of 71.06222, 42.41617, 63.12332 billion kilograms of red meat on average are the results of per unit increase in price of chicken, income and population respectively, whilst other variables unchanged This result indicates that for this sample, the price of red meat has a negative impact on the quantity demanded, while the other independent variables have a positive relationship with red meat quantity demanded, with the price of chicken having the largest marginal effect The coefficient of determination R-squared takes the value of 0.9454 indicates that 94,54% of the total variation in quantity demanded of red meat is explained by the four independent variables in this sample However, there is a problem with R2, it tends to increase each time we include an additional variable in the model, which might mislead to a better fit, known as an overfitting model That’s when we have adjusted R2, a modified version of R2, attempts to yield a more honest value to estimate the R2 for the population, measured the corrected goodness of fit of 93,94% of the model The standard errors associated with coefficients measure the average differences from the real value of data to the regression line, which is 12.9452, 58.613, 17.6377, 4.72514 units in terms of red meat price, chicken price, income and number of consumers respectively Moreover, there are sum of squares associated with the three sources of variance 203106561 of TSS is the total variation of the actual value of the dependent variable around their mean ESS takes the value of 192020954 is the variation explained by the regression model and RSS = 11085607.3 indicates the unexplained variation of the dependent values It can be inferred from the sample statistics that the model is relatively fitted and explanatory of our concerned relationship between dependent variable and independent variables Page 23 ECONOMETRICS REPORT KTEE218.1 GROUP 3.2 Statistical inferences 3.2.1 Hypothesis testing 3.2.1.1 Statistical significance of individual coefficients To test the significance of estimated coefficients of estimators we construct the following hypothesis testing, considering significance level of 5% 3.2.1.1.1 Price of red meat 1-sided test: Is the price of meat negatively related to the quantity demanded of that? 𝐻0 : 𝛽1 ≥ 𝐻1 : 𝛽1 < Test statistic: 𝑡𝑠 =-0.93 P-value=0.1785>0.05 => not reject H0 P-value is smaller than 𝛼, showing that there is not enough evidence to reject the null hypothesis 2-sided test: Does the price of meat have an impact on the quantity demanded of that? 𝐻0 : 𝛽1 = 𝐻1 : 𝛽1 ≠ Test statistic: 𝑡𝑠 =-0.93 P-value=0.357>0.05 => not reject Ho P-value is smaller than 𝛼, showing that there is not enough evidence to reject the null hypothesis 3.2.1.1.2 Price of chicken 1-sided test: Is the price of chicken positively related to the quantity demanded of meat? 𝐻0 : 𝛽2 ≤ 𝐻1 : 𝛽2 > Test statistic: 𝑡𝑠 =1.21 P-value=0.1165>0.05 => not reject H0 P-value is smaller than 𝛼, showing that there is not enough evidence to reject the null hypothesis 2-sided test: Does the price of chicken have an impact on the quantity demanded of meat? Page 24 ECONOMETRICS REPORT KTEE218.1 GROUP 𝐻0 : 𝛽2 = 𝐻1 : 𝛽2 ≠ Test statistic: 𝑡𝑠 =1.21 P-value=0.233>0.05 => not reject Ho P-value is smaller than 𝛼, showing that there is not enough evidence to reject the null hypothesis Considering there are not sufficient evidence to include indexes, price of red meat and chicken to the model, we then need to test the joint effect to confirm the necessity of adding those two as independent variables in the model 3.2.1.1.3 Income of consumers 1-sided test: Is income of consumers positively related to quantity demanded of meat? 𝐻0 : 𝛽3 ≤ 𝐻1 : 𝛽3 > Test statistic: 𝑡𝑠 =2.40 P-value=0.000 reject H0 At 5% of significance, income of consumers has a positive effect on quantity demanded of meat 3.2.1.1.4 Number of consumers 1-sided test: Is the number of consumers positively related to the quantity demanded of meat? 𝐻0 : 𝛽4 ≤ 𝐻1 : 𝛽4 > Test statistic: 𝑡𝑠 =13.36 P-value=0.0105 reject H0 At 5% of significance, the number of consumers has a positive effect on quantity demanded of meat Page 25 ECONOMETRICS REPORT KTEE218.1 GROUP 3.2.1.2 Overall significance of the multiple regression Hypothesis: Do all factors jointly explain the variation in the quantity demanded of meat? 𝐻0 : 𝛽1 = 𝛽2 = 𝛽3 = 𝛽4 = 𝐻1 : 𝛽1 + 𝛽2 + 𝛽3 + 𝛽4 ≠ Equivalent hypothesis: 𝐻0 : 𝑅 = 𝐻1 : 𝑅2 > Test statistic: 𝑅2 𝑘 𝐹𝑠 = = 155,89 − 𝑅2 𝑛−𝑘−1 Critical F: 𝐹0,05 (4,36) = 2,63353209 𝐹𝑠 > 𝐹𝛼 (𝑘, 𝑛 − 𝑘 − 1) => 𝑟𝑒𝑗𝑒𝑐𝑡 𝐻𝑜 At 5% level of significance, the model is statistically significant 3.2.1.3 Joint significance of the price of red meat and the price of chicken Unrestricted model: 𝐷𝑒𝑚𝑎𝑛𝑑𝑖 = 𝛽0 + 𝛽1 𝑃𝑟𝑖𝑐𝑒𝑖 + 𝛽2 𝐶ℎ𝑖𝑐𝑘𝑒𝑛𝑖 + 𝛽3 𝐼𝑛𝑐𝑜𝑚𝑒𝑖 + 𝛽4 𝑃𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛𝑖 +ui Hypothesis: Do the price of meat and price of chicken have a joint effect on the quantity demanded of meat? 𝐻0 : 𝛽1 = 𝛽2 = 𝐻1 : 𝛽1 + 𝛽2 > Test statistic: 𝐹𝑠 = (𝑅𝑢 − 𝑅𝑅 )(𝑛 − 𝑘 − 1) (1 − 𝑅𝑢 )𝑚 ≈ 0,791 Critical F: 𝐹𝛼 (𝑚, 𝑛 − 𝑘) = 𝐹0,05 (2,37) = 3,251 𝐹𝑠 < 𝐹𝛼 (𝑚, 𝑛 − 𝑘) => 𝑑𝑜 𝑛𝑜𝑡 𝑟𝑒𝑗𝑒𝑐𝑡 𝐻𝑜 Page 26 ECONOMETRICS REPORT KTEE218.1 GROUP There is not enough evidence to prove the significance of the joint effect of the price of red meat and price of chicken on the quantity demanded of red meat, we conclude that we should not add these two factors as independent variables to our model Restricted model: 𝐷𝑒𝑚𝑎𝑛𝑑𝑖 = 𝛽0 + 𝛽3 𝐼𝑛𝑐𝑜𝑚𝑒𝑖 + 𝛽4 𝑃𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛𝑖 +ui 3.2.2 Consistency of the regression results with the theories 3.2.2.1 Consistency of the regression result with the theories It can be derived from the regression result that the estimators have demonstrated a consistency with our economic theory basis in the section I of this essay The sign of first estimated coefficient is negative, showing that the price of red meat is negatively related with the independent variable, quantity demanded This result is consistent with the Law of Demand by N.G.Mankiw, in which price and quantity of a good have an inverse relationship Considering chicken is a substitute good, the ̂2 indicates a consistent relation with based theory Also, income positive sign of 𝛽 and number of consumer’s positive estimated coefficients proved a consistency to section I as well 3.2.2.2 Mechanism of the relationships between variables 3.2.2.2.1 Income of consumers and red meat quantity demanded In general, red meat has high production costs and high output prices when compared to other commodities Therefore, demand for red meat is associated with higher incomes (knowing that red meat is normal good) Per capita income has risen rapidly as a result of technological advancements and trade liberalization As 44 sovereign states in Europe are mostly high income and upper-middle income countries, the increase in red meat demand has stemmed from income growth, proving the positive relationship between income of consumers and red meat demand 3.2.2.2.2 Number of consumers and red meat quantity demanded Reality has shown that population dynamics drive consumption and demand The most crucial factor driving the expected increase in meat consumption demand is population growth Increases in the number of consumers with higher disposable incomes in the EU have been attributed to a change in diet, which includes more meat and dairy intake, causing the increase in red meat demand accordingly Thus, it is stated that the number of consumers is positively related to the quantity demanded of red meat Page 27 ECONOMETRICS REPORT KTEE218.1 3.2.2.2.3 Price of chicken and red meat quantity demanded GROUP Although chicken as a poultry has been known as a cheap and healthy product, red meat also has nutritional benefits itself Red meat is high in iron, protein, vitamin B12 and zinc, which keeps the immune system working properly, especially needed in the COVID-19 situation Therefore, red meat has been known as a substitute for chicken meat qualitatively and quantitatively Thus, a rise in the price of chicken encourages consumers to use an alternative substitute product, which leads to an increase in the quantity demanded of red meat Not to mention the European Union is one of the areas with the largest consumption of red meat in the world There is no doubt that the price of chicken has a positive impact on red meat demand 3.2.2.2.4 Price of red meat and its quantity demanded In accordance with the law of demand, a rise in the price of red meat induces the consumers to purchase less, considering that red meat is not a giffen good Thus, we agreed on the negative relationship between the price of red meat and its demand 3.3 Recommendation and conclusion 3.3.1 Recommendation These findings have significant implications on the development of red meat sector policies in Europe To increase the demand for red meat, governments in European countries should adjust the price of red meat to be sustainable Furthermore, in terms of demand response to income change, we establish that meat items are normal goods, and therefore their demand will rise as income rises Governments should apply suitable policies to increase income per capita of their citizens hence quantity demanded for red meat will increase As can be seen in our explicit explanations above, red meat is a significantly nutritious food that people can consume regularly Consumer preferences for red meat make domestic production and meat import much more necessary Every political entity's main purpose is to maximize overall economic prosperity for its citizens Greater economic welfare can be obtained with fewer barriers and less restrictive economic policies so that domestic and foreign companies can join the market to supply more meat for the European, which can meet the demand of all citizens The government should exert control over and establish legislation to regulate meat pricing in order to avoid unnecessarily high meat prices and to increase demand for meat Because of the high cost of meat production, the government should encourage the production of red meat and red meat products by lowering red meat prices and supporting livestock farmers with Page 28 ECONOMETRICS REPORT facilities KTEE218.1 GROUP 3.3.2 Conclusion This essay investigated factors (price of red meat, price of chicken, income per capita and population) influencing red meat quantity demanded The analysis has been carried out based on the theory of Demand Function Regression analysis model and Ordinary Least Squares (OSL) are used effectively to prove the theory The results suggest that red meat is a staple in the food baskets of city dwellers Any increase in pricing, along with a lack of compensating purchasing power, causes a decline in consumption patterns of these vital items, resulting in nutritional abnormalities and difficulties as a result of the lack of protein intake With an R2 value of 0.9454 for our regression model, it is true that our regression explains fully red meat demand for European countries Our model can explain 94,54% of the total variation in the independent variables After analyzing background information, a model was constructed that helps determine some possible influences for red meat quantity demanded Applying the law of demand, it is shown that the price and quantity demanded is a negative relationship Price fluctuations could alter red meat demand All things considered, we also find compelling evidence that nations with lower levels of population size have lower demand for red meat in Europe Chicken is a substitution for red meat, rational people will consume the one at a lower price compared to the other Red meat is a normal good so with higher income, people will consume more red meat In conclusion, only its price will have an adverse impact on red meat demand Other variables have a positive relationship with red meat quantity demanded Page 29 ECONOMETRICS REPORT KTEE218.1 GROUP REFERENCES Database on Numbeo, Price Rankings by Country of Beef Round (1kg) (or Equivalent Back Leg Red Meat) (Markets) https://www.numbeo.com/cost-ofliving/country_price_rankings?itemId=121&fbclid=IwAR0xx6XU1c2LKDN6V-VG74Pyj_UHP5vVnA3j2UfRBDY2kj_Ujh10djLx8M (accessed on 22 September 2021) Database on Numbeo, Food Prices, https://www.numbeo.com/foodprices/?fbclid=IwAR3-x_hroHF-0GNrsl92HGqSNUG1vVIynnoMZEzFkJmwW2dxooCsnFIXzg (accessed on 22 September 2021) Website of The World Bank, Population, total - European Union, https://data.worldbank.org/indicator/SP.POP.TOTL?end=2017&locations=E U&most_recent_year_desc=false&start=1960&fbclid=IwAR32Eq02BEtjM O9rP8Mnt4bwWc0zQLK9gDnSq8mZjSuLUqb393FG0HocuMs (accessed on 21 September 2021) Website of The World Bank, GDP (current US$) - European Union, https://data.worldbank.org/indicator/NY.GDP.MKTP.CD?locations=EU&fb clid=IwAR1eOMDdDziWr7aPX4MdJIi4qYxb4Wv-cNBeIONCut4-7Klo8NYXOX92so (accessed on 21 September 2021) Hannah Ritchie and Max Roser, 2017 Meat and Dairy Production Published online at OurWorldInData.org Retrieved from: https://ourworldindata.org/meat-production Website of Food and Agricultural Organization of the United Nations (FAOSTAT), Food Balances (2014-), http://www.fao.org/faostat/en/?fbclid=IwAR2uvSCSSBEaoNQljmENl32Nz3 gC4dstnxhryLISAEkVrNeyzb-t3dOBvvk#data/FBS (accessed on 21 September 2021) Page 30 ECONOMETRICS REPORT KTEE218.1 APPENDIX Regression result Descriptive Statistics Page 31 GROUP ECONOMETRICS REPORT KTEE218.1 GROUP Correlation matrix Joint effect testing between price of red meat and the price of chicken Page 32 ECONOMETRICS REPORT KTEE218.1 Regression result for restricted model Do-file Page 33 GROUP ECONOMETRICS REPORT Dataset for the research Page 34 KTEE218.1 GROUP