Empirical Analysis on the Influential Factors of Real Estate Price: A Panel VAR Model View

The cities in China have had a period of great prosperity and rapid economic growth due to marketization of housing policy since 1998. This paper empirically compares the relationship between economic fundamentals and non-economic fundamentals and real estate prices by establishing a panel data VAR model from 2005 to 2015. This paper adopts the data of real estate prices, economic factors, and non-economic factors in 31 provinces and cities, and the panel VAR model to examine the explanatory power of relevant influencing factors by the panel VAR model impacted on the house prices. The results indicate that the economic factors significantly have impact on rising real estate prices while the non-economic factors do not significantly have impact on rising real estate prices. This research concludes that if the change in real estate prices declines, the real estate prices, land supply, income and real estate development loans will increase. Yet the inflation rate will go up if the change in real estate prices rises. The contribution of this study provides some policy suggestions on the situation of the Chinese real estate market. Keywords—Real Estate Prices; Panel VAR Model (PVAR); Economic Factors; Non-economic Factors

INTRODUCTION
The cities in China have had a period of great prosperity and rapid economic growth due to marketization of housing policy since 1998. Owing to the influx of rural population, urban population have been increasing and further promoted the rapid development of the real estate industry in China. As a result, the real estate industry in China gradually evolved into the national pillar industry. In 2000, China began to have certain norms in the real estate market. The "land reform" in 2002 was publicly traded adopting the land agreement transfer method. The Measures for the Administration of Affordable Housing were officially implemented in 2004.
In recent years, China regulated the real estate market and even stimulated consumption and prosperity of the real estate market. After 2004, real estate prices rose rapidly and the government began to curb the rise in real estate prices. From "State 8" in 2005 to "New State 5" in 2013, most of the controlling policies are measures to curb real estate prices. During this period, the real estate market was briefly suppressed during the financial crisis of 2008, and the government introduced some policies at this time to make the real estate market develop steadily. After 2009, the real estate market quickly out of the downturn brought by the financial crisis, housing prices rebounded rapidly. Then, China began to implement "restriction order", and as a basic means of regulation of the real estate market. At the 19th Communist Party of China (CPC) National Congress in 2017, General Secretary Xi Jinping also responded to the housing policy and put forward the principle of "insisting that the house should be used for housing rather than for speculation and speeding up the establishment of multi-agent supply, Multi-channel protection, rent and purchase of both housing system, so that all people live in.".
The rapid development of Chinese real estate has made a contribution to its economic growth in recent years. Because of the unscientific management and policy implementation, the speculation of real estate developers and consumers makes the real estate prices rising unreasonably. From the Panel VAR data, the national average real estate sales price rose extremely from 15,200 per square meters in 2005 to 22,630 per square meter in 2015. However, with such a rapid rise, many problems to be solved have emerged in the development of the Chinese real estate market in the recent 20 years.
First, the real estate market supply is greater than its market demand. And because of the difference of urban and rural development in China, the demand for housing in urban and rural areas has always been very different, which further leads to the unbalance of supply and demand in Chinese real estate market. Second, the inventory of the Chinese real estate market is still too high. After the "supply-side reform" was started, the "de-stocking" in the first-tier cities had achieved good results. However, in the second and third-tier cities, the "de-stocking" policy did not achieve very good results. In general, the high inventory situation has been improved, but it is still a major problem in the Chinese real estate market. Although the government defines the scope of the revenue to purchase the affordable houses, there are a lot of affordable houses for sale and existing rent-seeking behavior due to unscientific supervision and some real estate developers' profit intention. So that some affordable housing has been turned into an investing housing.
In recent years, the rapid development of real estate made great contribution to the Chinese economy. Because of the unscientific management and no specific policy implementation, the speculation of real estate developers, buyers, and other factors make the real estate prices rise unreasonably. With such a rapid rising, although the Chinese real estate market has been developing in nearly 20 years, there have been many problems to be solved.
First, there is a supply and demand imbalance problem in the real estate market. The supply of the real estate market is more than its market demand. And because of the difference of urban and rural development in China, there has always been a difference between the demand for housing in urban and rural areas, which further leads to the imbalance of supply and demand in Chinese real estate market. Second, the inventory in the real estate market is still too high. In general, the high inventory situation has been improved, but it is still a major problem in the Chinese real estate market. Finally, there is a protection of housing issues problem due to unscientific supervision and housing developers tend to unreasonable profit such as speculating affordable housing into an invest housing. Therefore, Chinese real estate markets need more scientific and effective control policies such as a macro-control policy to solve these problems. [6] Real estate has always been one of the more important aspects of China, and there is a wide variation in provinces and municipalities. The purpose of this paper conducts research and analysis on the influential factors of real estate prices across the country to understand the impact of changes in real estate prices on economic factors and non-economic factors, based on the data of various provinces and cities in China from 2005 to 2015. The structure of this paper is as follows: the first part is the introduction about the Chinese real estate; the second part is the literature review; the third part is the theoretical model setting and results; the fourth part is the policy implication and conclusions.

II. LITERATURE REVIEW
Before the empirical analysis, it needs to analyze the impact of changes in real estate prices on the economy in China, and then study the influent factors of real estate prices on the real estate prices. Therefore, it can be more clearly and reasonably regulated a real estate price policy in China. After more than ten years of real estate market development, the real estate industry has become a pillar industry, which is closely related to Chinese economic development. However, the rapid rise of the real estate prices has also caused many problems on the Chinese economic development and has also brought unfavorable effects on the people's livelihood. Therefore, before studying the effect of influencing factors on real estate price, it is necessary to research these factors affecting real estate prices.

A. The impact of Real Estate Price Changes on Real Estate
Price The expected price of real estate is based on the historical price and growth rate of the real estate price. Therefore, the rise of the real estate price will cause people to have an expectation of rising. At the same time, investors also have a rise in the future real estate price expectations. As a herding effect in the real estate market, investors shall be able to earn the difference between the purchase of housing, which also makes the real estate prices prone to abnormal changes. [4] B. The Impact of Land Supply on Real Estate Prices Land resources in China have been under the control of the government, and the land resources are limited resources. In the short term, real estate prices can be restrained by increasing the supply of real estate. However, in the long run, the cost of land is also getting higher, which also leads to a faster rebound in real estate prices. Therefore, the supply of land on the real estate prices, the short term can curb real estate prices, but in the long-run real estate prices will rise.

C. Inflation Rate Impacting on Real Estate Prices
It is necessary to analyze different aspects of the impact of the inflation rate. On the one hand, the inflation rate will affect the rise of the price so that the price of construction materials will rise, thus affecting the construction cost and affecting the real estate price. [3] On the other hand, many investors regard houses as a commodity against inflation, which in turn adds to many real estate prices, which in any case have led to higher real estate prices.

D. Impact of Real Estate Development Loan on Real Estate
Price The more real estate development loans increase, the more real estate investors will promote the amount of real estate funds and lead to different effects of the real estate price. On the one hand, real estate investors in the short term do not need to sell houses as soon as possible, hoping to make more money, under the situation of the increase in the price of housing; on the other hand, the wealth of investors can also greatly increase the supply of real estate, which also makes real estate prices lower, but the impact of this takes time to be effective, Thus, real estate development loans in the short term can increase real estate prices; in the long-term, increase the supply of real estate reduce the price of its real estate. [8] E. The Impact of Income on Real Estate Prices Increased income will increase people's purchasing power, thereby increasing people's rigid demand for real estate prices, which is the main reason for real estate prices. Rapid economic development in China, people's income is also continuing to grow, which also makes Chinese real estate prices at a high level. [1]

F. The Impact of Investment in Real Estate on Real Estate
Prices On the one hand, the consumption of building materials is likely to be the result of an increase in construction prices, which will have an effect on the rise of real estate prices. On the other hand, the increase in investment in social housing projects will increase some real estate supply and has eased some rigid demand, which leads to a decline in real estate prices. [7] However, in some areas, the distribution of affordable housing is unscientific, resulting in some idleness, leading to an increase in real estate prices in the long run.
In general, the price of real estate will remain at a relatively high level for a long time due to the increase of income, and more factors will cause real estate prices to rise. Therefore, it is necessary to have a deeper understanding and analysis of these Advances in Economics, Business and Management Research, volume 96 factors and thus avoid abnormal changes in real estate prices, reducing the adverse impact.

A. Model Variable Data Source and Processing
Taking into account the economic factors and noneconomic factors and the relationship between real estate prices, some of the factors that are national, so this paper selects the provinces where the data can be analyzed. Therefore, this article chooses the price itself, the per capita income and the inflation rate in the economic fundamentals; selects the six factors of credit policy, land policy and social security policy in the non-economic factors to be analyzed.
In the economic factors, this article adopts the sales area of the province's real estate and sales amount of real estate to find out the average provinces' sales prices; per capita income selected in urban provinces is per capita disposable income; inflation rate selected is the province's Consumer Price Index (CPI) year-on-year growth rate. In the non-economic factors of the influencing factors, this article adopts the real estate investment loans representing the amount of real estate development loans; the land turnover in each province means the amount of land supply; the real estate investment in public welfare describes the protection of housing investment amount. This paper adopts annual data from 31 provinces, autonomous regions and municipalities directly based on the Central Government from 2005 to 2015. In order to eliminate heteroscedasticity, the data in this paper are all logarithm, and the rate of data change of the logarithm is adopted for research and analysis. From the above data, we can see the average, standard deviation, minimum and maximum of each variable. Based on these data, we can see that these factors in different regions have changed greatly in ten years, resulting in a dispersion of all data extremely.
1 the average provinces' sales prices 2 the amount of land supply 3 the real estate investment loans 4 per capita disposable income 5 the real estate investment in public welfare

B. The Choice of Model
Although the IV-GMM method can be used to reduce the endogeneity, the endogeneity cannot be completely eliminated. The panel VAR model, which has both the advantages of the panel data model and the time-series VAR model which can eliminate the endogeneity. Not only individual and time effects are considered, but also the impact of variable impact on other variables can be analyzed. Therefore, this paper adopts panel VAR (PVAR) model to study and analyze the relationship real estate prices between economic factors and non-economic factors and uses its impulse response to analyze the response of real estate prices in the face of impact. PVAR model and its Stata code firstly introduced by Love. [2] Stata12.0 software is also adopted to analyze the variables.

A. Panel Unit Root Test
In time series, the purpose of the unit root test is to avoid testing the un-stability of the time series for regression. Since the panel data includes both the characteristics of the crosssection data and the characteristics of the time series, the stability of the panel data needs to be checked to overcome the small-sample bias of a single time-series unit root test, thereby reducing to some extent unobservable individual effects and cross-sectional correlations. This article adopts the Levin-Lin-Chu (LLC) test provided in the Stata software to perform a unit root test on panel data. The results are shown in the following table.

B. Panel Lag Choice of VAR Model.
Before the parameter estimation is performed, it is first necessary to select the lag order of the PVAR model. This paper adopts AIC, BIC, and HQIC information criteria to select the optimal lag order according to the minimum criteria in the guidelines. Hysteresis order selection results as follows:

C. Graphical Analysis of Panel Impulse Response
The paper studies the impact of influencing factors on real estate prices, which includes two aspects: firstly, the impact of economic factors on the equilibrium prices of real estate. Reflected in the model, namely, the equilibrium price of real estate, per capita disposable income of urban households and the impact of inflation on the equilibrium price of real estate; secondly, the impact of non-economic factors on the equilibrium price of real estate. Real estate development loans, land supply and the change of developing protection house investment impact on the equilibrium price of real estate. Therefore, the above two aspects are separately analyzed according to the impulse response diagram (IRF) in Stata software. The following impulse response plots show the lag order of the shock, due to the annual data, the lag first order represents one year, the vertical axis represents the response of the response variable, and the solid line represents a variable over time impulse response to standard deviation information of another variable, dashed line indicates the confidence band on both sides of the response pulse pattern or minus two standard deviations, due to the government's macroeconomic plan of 5 years, the following pulse patterns are all defined as 5 issues. The data at this time is taken as the logarithm, and the graph shows the effect of the change of the factor on the real estate price. First, analyzing the change in the real estate equilibrium price impacted on the change of real estate prices. Judging from the direction of change, after the current period of a positive impact on the real estate equilibrium price, the change in the rate of change of Chinese real estate equilibrium price appears as a response of falling, then rising and then falling, and then positively and negatively then positively, Finally, a phenomenon of negative response. In terms of responsiveness, the highest value is 0.8% of the first period. From the response time point of view, the response time is basically to the third period.
From the above three aspects, under the positive impact of the real estate equilibrium price itself, the real estate price in the early stage is greatly influenced by the fluctuation of its own price, which may be due to the people's forecast of the real estate price and the increase of the real estate price to its own influence. After the first two years, the government intervened in the real estate price changes, the impact of the increase of real estate prices on real estate prices began to decrease. Finally, its effect gradually weakened.
Secondly, analyzing the change in land supply impacted on the change in real estate prices. From the change direction, the current supply of land to a positive impact, the changes in real estate prices, firstly negative to positive and negative after a response. From the perspective of response intensity, the highest level of change was 0.02% in the first period. From the response time, the duration is more than five periods. From the above three perspectives, under the impact of a positive change in land supply, the growth rate of real estate prices will slowly decline in the early period. In the second to third periods, the change in real estate prices will be affected by the supply of land. The smallest, and then in the fourth year when the real estate price changes affected by the impact of land supply increased, and finally in the fifth year of its effects have a downward trend. This is because the development of land into real estate takes a certain period of time, so the increase in land supply in the first two years has reduced the impact on real estate prices, and in the third year, the increase in land supply has turned into real estate supply. At this point, the impact of changes in land supply on real estate prices slowly strengthened. Thirdly, analyzing changes in inflation rate impacted on the rate of change of real estate prices. In terms of the direction of change, under the positive impact of the current inflation rate, the growth rate of the real estate price is going to be followed by the positive and negative response to the negative. From the strength of the response, the highest value of the change was 0.03% in the first and third periods. From the response time, the duration is more than five periods.

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From the above three aspects, the positive changes in the inflation rate, and the impact of real estate prices two years ago are relatively large, and the impact of the back gradually becomes weakened. It is possible that the rise in the inflation rate leads to an increase in the construction materials for real estate, thus making real estate prices more likely to be affected by the inflation rate. For the government central bank can curb rising inflation and adopt the tighter monetary policy, the real estate prices by the impact of inflation have declined. So in the long run, the impact of inflation on real estate prices lower and lower. Fourth, analyzing the impact of changes in real estate development loan amount on the rate of change of real estate prices. From the perspective of change, under the positive impact of the current loan amount on real estate development, the growth rate of real estate prices shows a positive-negative and a negative-positive response, and the positive response is lower than the negative response. From the point of view of response intensity, the highest value of its change was 0.04% in the second period. From the time of response, it lasts for more than five periods.
From the above three aspects, real estate prices by the growth of real estate development loans increases, and then weakens at a larger margin, and its influence is slowly reduced. This may be making real estate developers have sufficient funds, due to the increase in real estate development loans in a year. So they do not have to rush to sell the house. As the sales price increases, the impact of this time is slowly increasing in the long term. The real estate development loans will increase when the amount of real estate supply will increase, helping to curb real estate prices, so the impact of the real estate development and investment at this time on the real estate prices is significantly weakened. Fifth, analyzing the influence of the change of per capita disposable income of urban households on the rate of change of real estate prices. In light of the change direction, the performance of the growth rate of real estate prices has been negatively impacted by a positive impact on per capita disposable income of urban households in the current period. From the response strength, the highest response in the second phase is 0.05%. From the response time point of view, the impact of time after the fifth period becomes weaker than previous period. From the response strength, the highest response in the second phase is 0.05%. From the response time point of view, the impact of time after the fifth judging from the above three aspects, based on a positive impact on per capita disposable income of urban households, the change in real estate prices has been weakened over a period of five years, which shows that in the case of people getting rich. The increase in income does not mean that people will reinvest additional income into the real estate market, making the impact of income on real estate prices getting lower and lower. Sixthly, analyzing the impact of the changes in the investment of social security on the rate of change of real estate prices. Judging from the direction of change, under the impact of a positive investment in the amount of affordable housing in the current period, the growth rate of real estate prices will be positively followed by a negative and then positive response. In terms of response strength, the highest response value is 0.001% in the first phase. From the response time point of view, short-term impact, the long-term effect is relatively large.

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From the above three perspectives, the effect of a positive change in the amount of investment in affordable housing on real estate prices has been increasing in the first two years, while the subsequent effects have been relatively weak. This may be due to the fact that the increase in the amount of this investment in the short term has affected the increase in construction costs. At this time, it has a direct impact on real estate prices, so its effect has been increasing. After two years, the completion of the security housing has increased the supply of housing and eased the rigid requirements of real estate. Therefore, the effect is reduced at this time, and even a negative effect will occur. Therefore, the price of real estate will decline accordingly. However, in the long run, insufficient investment in affordable housing will increase the price of affordable housing, which will affect the rise in real estate prices. Therefore, the degree of impact after five years will increase.

A. Policy Implication
From the above study, it is difficult to intervene between the real estate prices itself and the income factor. As for the inflation rate factor, the increase will definitely cause the government to adopt a tightening monetary policy, which will lead to a drop in real estate prices. The effect of the long-term policy will also gradually weaken, eventually bringing the impact of inflation on real estate prices close to zero. Therefore, the following three factors should be proposed in the following three policy recommendations:

1) Land Policy
The rise in land prices has always affected the rise in real estate prices. According to the arrangement of Chinese first land finance system, local governments often strictly control land supply scales through the combination of "recruiting", "patching" and "hanging" methods, controlling in shortage of land supply and rising land prices. At the same time, rising land prices will lead to rising real estate development costs, which in turn will drive up real estate prices. Therefore, the government should expand the supply of land in order to curb the excessive increase in land prices caused by insufficient land supply. The system of restricting land development in the secondary market and implementing deadlines can be adopted to crack down on private capital and developers in their efforts to cut downland and copy land.

2) The Amount of Real Estate Development Loan
Its impact on real estate prices is a short-term increase, but it will reduce real estate prices in the long run. Therefore, the government can appropriately increase the amount of real estate development loans, but the increase in loan amount should not be excessive, and in order to prevent adverse effects, the impact in the short term must be within the scope of economic changes. Although house prices have risen in the short term, for the long-term, the increase in the amount of loans for real estate development has a good effect on the suppression of real estate prices. Therefore, the government needs to increase the amount of loans.

3) Safeguard Housing Policy
The impact of the construction of affordable housing on the real estate industry is also an important factor because the construction of affordable housing directly affects the rigid demand of the real estate industry and can fundamentally restrain the rise in real estate prices. However, there is also a need for certain plans for the construction of affordable housing to prevent intermittent investment in affordable housing. In addition, when the protection housing policy is implemented, the government needs to pay attention to the distribution of the security housing after the housing is built. The scientific allocation of affordable housing to avoid the problem of idleness in security housing allows this policy to achieve the best results.

B. Conclusion
This paper adopts the data of real estate prices, economic factors, and non-economic factors in 31 provinces and cities, and the panel VAR model to examine the explanatory power of relevant influencing factors by the panel VAR model impacted on the house prices.
Specifically, the author proposes recommendations as follow. Firstly, changes in real estate prices are significantly affected by prices themselves, inflation, and income. Among these three factors, within two years, the changes in real estate prices and changes in the inflation rate have a greater effect on real estate prices and the best effects within the first two periods. Two years later, the effects of these changes will slowly decrease. The impact of income on real estate in recent years has been reduced. Secondly, of the six factors studied in this paper, in addition to the impact of land supply and income,

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the impact of the other four factors on real estate price changes in the previous two years has been increasing, and most of them have been in the previous two years. Its effect has reached its maximum, and its effect has been gradually weakened after two years.

ACKNOWLEDGMENT
The author thanks Pro.Love for his Stata code and the editor and anonymous referee for their comments.


Analysis of Trade Costs and FTA Effects on Bilateral Trade Flows in the Southern African Development Community

The study measured the relative effect of the SADC FTA, logistical and governance induced trade costs on trade flows, using a gravity model based on the Pseudo-Maximum Likelihood (PPML) estimations, covering the period 2005 to 2014. The study did not find evidence of trade creation by the SADC FTA, but found robust evidence regarding the trade diverting effects of the SADC FTA. Additionally, the study suggests that improvements in governance and reductions in logistics related costs raise trade flows. Further, trade indicators show that the SADC FTA resulted in increased intra-SADC trade intensity, implying a growing consumer market and potential enhancer of growth in the region.

estimated various versions of the gravity model with varying estimation methods to infer bilateral trade costs while other studies estimated directly, different measures of trade costs on trade flows. Most of these studies did not include African countries and let alone SADC countries in their data sets, and thus, little is known about the different trade barriers that hamper intra-SADC trade.
A study by Jacks, Meissner and Novy (2011), employed a micro-founded measure of trade frictions such as, exchange rate regimes, and a gravity model with ordinary least squares (OLS) method, to test the importance of bilateral trade costs in determining international trade flows. By sampling 130 country pairs from the Americas, Asia, Europe and Oceania from 1870 to 2000, they demonstrated that declining trade costs where vital to the pre-World War I trade boom while the post-World War II trade boom was mainly, determined by changes in output. On the other hand, a study by Hoekman and Nicita (2008), used a gravity regression framework with PPML estimations for 2006 data for 104 importers and 115 exporters to estimate the impact of tariffs, NTBs, LPI, domestic trade costs and other trade barriers on trade flows. They found that tariff and NTBs were a significant obstacle to trade flows for low-income countries despite preferential access programs. Wilson, Mann and Otsuki (2004) used gravity equations to examine a relationship between trade facilitation and trade flows across 75 countries and found that improvements in trade facilitation would increase trade. Yotov (2012), Lin (2013), and Lin and Sim (2012) focused on estimating the negative impact of distance on trade flows that increased over time when a gravity model was estimated using OLS. Using a gravity model with alternative estimation methods to the OLS, they showed robust evidence of a downward trend of the impact of distance on trade. Dutt and Traca (2010) analyzed a gravity model with OLS estimations, from 1980 to 2004 for 28 industrial sectors in 122 countries and included corruption to assess its impact on bilateral trade. This is because empirical studies had suggested that corruption was a barrier to trade. They found the effect of corruption to be ambiguous and contingent on tariffs, as their results suggested that the marginal effect of corruption on trade was enhancing in high tariff environments.
Studies by Bergstrand (2007, 2009) estimated the original European Economic Community (EEC) and Central American Common Market (CACM) with data from 1960 to 2000. Used a gravity model to estimate the effects of FTAs on trade flows. They found that FTAs, on average increased members' bilateral trade flows overtime. Other studies by Anderson andvan Wincoop (2003, 2004), Anderson (2011), Anderson and Yotov (2008), De Bruyne, Magerman and Van Hove (2013, and Bergstrand, Egger and Larch (2013) used a structural gravity model to estimate unobserved trade costs using data on trade flows and observable trade costs such as distance, borders, language, and multilateral resistance factors. They highlighted the effects of distance, borders, multilateral resistance, and other observable trade costs, while confirming the restrictiveness of a structural gravity model despite structural gravity theory's robustness in empirical research on disaggregated trade flows with missing or non-credible data.
Regarding the estimation techniques appropriate for the gravity models, several studies by Santos Silva and Tenreyro (2006), Martínez-Zarzoso, Nowak-Lehmann and Vollmer (2007), and Gómez-Herrera (2013) compared OLS, Gamma pseudo-maximum-likelihood (GPML), a Non-Linear Least Squares (NLS), PPML, and other estimation techniques' performance in constant elasticity models. Studies by Martínez-Zarzoso, Nowak-Lehmann and Vollmer (2007) found that there was no 'best' estimator and highly recommended to follow a model selection approach using a number of tests to select the more appropriate estimator for any application. Most recent studies by Santos Silva and Tenereyro (2011), Bosquet and Boulhol (2009), Prehn, Brümmer and Glauben (2012), and Fally (2015 confirmed Santos Silva and Tenreyro (2006) claim that the PPML technique is the appropriate estimator for constant elasticity models such as the gravity models in the presence of zero trade flows and heteroscedasticity. While the OLS estimation technique of log linearized models was found to overstate the magnitude of the coefficients. They dismissed the claim of no best estimator by Martínez-Zarzoso, Nowak-Lehmann and Vollmer (2007) who used data sets that were not for constant elasticity models.
The empirical literature reviewed have limitations that this paper attempts to address. The previous studies did not include a large number of African countries in their data sets, let alone SADC countries, mostly focussing on high and some middle income countries. African and SADC countries are either middle income or low income countries that are usually excluded by most studies. Studies that covered Africa, are limited in coverage of SADC and very little is known about the effects of governance and logistical related costs with regards to the SADC FTA that was launched in 2008 and fully implemented in 2012.

III.Methodology A. Model
To assess the impact of trade costs and the SADC FTA on trade flows, this chapter utilizes a gravity model similar to Anderson and van Wincoop (2003), and Fally (2015), that included multilateral resistance terms in their models. The gravity framework predicts that the volume of trade between any two countries will be positively related to the size of their economies (usually measured by GDP) and inversely related to the trade costs between them, such as distance (Frankel, 1998). At an empirical level, such a model has proved successful in predicting the pattern of Studies such as Hoekman and Nicita (2008), Jacks et al. (2011), Kimura andLee, (2006),and Wilson et al .(2004) that included various trade costs related to policy, economic and political environment in their models, found them to have an effect on the flow of trade. Generally, literature supports the hypothesis that, besides tariffs and NTBs, other trade costs related to the economic and governance/political environment are significant determinants of trade flows between countries. This study builds on the existing literature using gravity models to investigate the importance of the SADC FTA and trade costs related to the economic and political environment in determining trade flows.
This study uses a gravity model that includes panel data of time invariant trade impediments (distance, contiguity, common language, colonial ties, landlockedness), as well as trade policy, economic and political environment trade cost variables. The study also includes multilateral resistance term proposed by Anderson and van Wincoop (2003) proxied by "remoteness" variables following Hoekman and Nicita (2008). A now widelyused strategy following (Santos Tenreyro 2006, 2011), is to estimate a constant elasticity model such as the gravity model using Poisson pseudo-maximum-likelihood (PPML) estimation method. Therefore, this study estimates a gravity equation using PPML as the main estimator, and fixed effects and pooled OLS as the alternatives. The PPML estimator produces consistent estimates in the presence of zero trade flows and heteroscedasticity, and is more robust to truncation. This study estimates the following gravity model: (1) Where， is the bilateral imports in levels between country m and country x in year t; is the natural log of importer country's GDP in year t; is the natural log of exporter country's GDP in year t; is the natural log of importer country's GDP per capita in year t; is the natural log of exporter country's GDP per capita in year t; is natural log of the geographic distance between the capitals of country m and country x; < = > refers to a dummy variable indicating contiguity between country pairs; < ?@=> refers to a dummy variable indicating whether the country pairs share a common official and second language(s); < < ? refers to a dummy variable indicating whether the country pairs had a common colonizer; ?@= ? refers to a dummy variable indicating whether the importing country is landlocked; ?@= ? refers to a dummy variable indicating whether the exporting country is landlocked; is natural log of the remoteness or relative distance of the importing country; is natural log of the remoteness or relative distance of the exporting country; A is the political stability index of the importing country in year t; A is the political stability index of the exporting country in year t; B is the logistics performance index of the importing country in year t; B is the logistics performance index of the exporting country in year t; C is the number of documents required per shipment to import goods ; D is the number of documents required per shipment to export goods; A refers to the trade policy dummy variable that takes the value 1 if both exporting and importing countries are members of the SADC FTA at time t, or if the importing country is a member of SADC FTA and zero otherwise; : refers to year fixed effects; ; is the error term; m is the importer (reporter/destination) country subscript; x is the exporter (partner /origin) country subscript; and t is the year subscript.
The study also analyzed trade Interdependence indices to add more insights to the gravity model estimations. Trade intensity and Introversion indices were analyzed. Intraregional trade intensity (HI) is defined as the intraregional trade share divided by the share of the region's total trade in world trade. The closer the HI is to the value of 1, then the more neutral the regional members' trade is. In other words, the region tends to not have any bias toward trading between its members or with outsiders. If the indicator is more than 1, then the region has a bias toward trading within itself; if the indicator is less than 1, then the region has a bias toward trading with outsiders. The HI will tend to rise when the share of a region's trade within itself rises faster than its share of world trade 1 . The following is the formula for the intra-regional trade intensity: where Tii = exports of region i to region i plus imports of region i from region I; Ti = total exports of region i to the world plus total imports of region i from the world; Tw = total world exports plus total world imports Extra-regional trade intensity (HE) index measures the trade intensity of countries in the region with those outside, calculated as the extra regional trade share divided by the share of the region's total trade in world trade. The closer the HE is to the value of 1, then the more neutral the regional members' trade with the outsiders. In other words, the region tends to not have any bias toward trading between its members or with outsiders. If the indicator is more than 1, then the region has a bias toward trading with the outsiders; if the indicator is less than 1, then the region has a bias toward trading within itself. The HE will tend to rise when the share of a region's trade with outsiders rises faster than its trade within itself. The following is the formula for the extra-regional trade intensity: Where Tii = exports of region i to region j plus imports of region i from region j; Ti = total exports of region i to the world plus total imports of region i from the world; Tw = total world exports plus total world imports Regional trade introversion (RTI) index measures the relative intensity of regional trading versus trading with outsiders. Intraregional trade intensity (HIi) and extra-regional trade intensity (HEi) are functions of the region's share of outsiders' total trade and not of world trade as in the previous trade intensity index. The index's range is -1 to 1 and it is independent of the size of the region. The index rises (or falls) only if the intensity of intraregional trade grows more (or less) rapidly than that of extra-regional trade. If the index is equal to zero, then the region's trade is geographically neutral. If it is more than zero, then the region's trade has an intraregional bias; if it is less than zero, then the region's trade has an extra-regional bias 1 .
The following is the formula for the regional trade introversion index: Tii = exports of region i to region i plus imports of region i from region i Ti = total exports of region i to the world plus total imports of region i from the world TOi = exports of region i to outsiders plus imports of region i from outsiders TO = total exports of outsiders plus total imports of outsiders

B. Data
The list of countries covered is reported in Table 9  ⁄ is the ratio of the exporting country's GDP to world GDP (UN and WTO, 2012). Information on the membership to SADC FTA comes from SADC (2011). Table 12 in Appendix I displays the SADC membership. Finally, to account for economic and political environment trade costs, the study utilizes the LPI as in Hoekman and Nicita (2008), as well as the number of documents to import and export (DM and DX) to capture further transaction costs and the political stability indices (PS) to capture governance and political environment effects, because of the volatile political environment among SADC countries. Data on the LPI and number of documents to import and export is from the World development indicators (World Bank, 2015), while the data on political stability indices comes from the World Bank's Worldwide Governance Indicators (WGI) (World Bank, 2015).In cases were the data values' range were deemed to be too large by Stata for convergence to occur, it was rescaled as an option in Stata. Although this affects the scale of coefficients and standard errors, it does not affect the significance and interpretation of results (Woodridge, 2013). For GDP, GDPPC, distance and relative distance, natural logarithms were used to rescale just as in Hoekman and Nicita (2008) and Santos Silva and Tenreyro (2006). LPI and Political stability indices were also rescaled to reduce the range of the data valuse using a commonly used rescaling formula 2 . SADC intensity index has been steadily rising since 2005 while the extra-SADC trades intensity index has been on a steady decline. This implies that SADC countries have a bias towards trading within themselves. The reasons for this bias is explained by the gravity model results in the next sub-section.

Figure 1 Extra-SADC Trade Intensity and Intra-SADC Trade Intensity
Figure 2 below graphs the regional trade introversion index for SADC from 2005-2014. The index after 2008 has been at slightly over 0.9 and at around 0.89 before 2008.The sharp change after 2008 is notable, reflecting the effect of the SADC FTA. The index clearly shows the intra SADC trade bias which grew after the launch of the FTA in 2008, implying that the intra-SADC trade intensity grew more rapidly than that of extra-SADC trade. Table 1 below present results from the PPML estimations, with the value of imports as the dependent variable, and shows coefficients of the regular gravity equation variables with coefficients of additional variables for this study. Equations 1 to 4 shows PPML estimates that take into account the effects of politics, logistics performance and the number of documents required for imports and exports. 1 . The regular gravity model variables have the expected signs and are statistically significant for all the equations, except for common language, which was dropped from the results presented in Table 1 below. GDPPC and remoteness were dropped from the estimations due to solve the problem of multicollinearity. GDP coefficients are, highly statistically significant with the exporting countries' GDP coefficients less than the importing countries' coefficients, and is similar to the study by Hoekman and Nicita (2008).  Distance has the expected negative coefficients that are significant at 1%. The negative distance coefficients highlight that trade between countries pairs that are closer to each other will be greater than trade between country pairs that are far apart. This is probably one of the reasons why SADC countries trade more with the EU 28, Africa and China compared to its trade with the USA, the largest economy in the world 1 . Therefore, distance is vital for trade flows to increase between country pairs, regardless of whether they are in a regional integration arrangement or not.

Source: Authors own calculations from UN Comtrade database B. Gravity Model estimation results
The contiguous (contig) has the expected positive sign and statistically significant at 1%. This implies that countries that share a common border (such as most SADC FTA members) tend to trade more than countries that don't share a border. Similarly, landlocked dummy has the expected negative sign and is statistically significant at 1%. Additionally, landlockedness coefficients for exporting countries are larger than those for importing countries. This implies that landlocked countries tend to trade less, especially when it comes to exports. About 50% of the SADC FTA members are landlocked, and therefore, intra-SADC FTA trade is potentially reduced.
Trade between countries that had a common colonizer is high as shown by the coefficients for comcol that have expected signs and statistically significant for all the equations. Common colonial ties has larger coefficient when the additional gravity model trade costs are accounted in the regression such as equation 1. Particularly, the inclusion of LPI increases the size of the coefficient for common colonial ties, implying that logistics efficiency, of customs clearance process, quality of trade and transport related infrastructure, ease of arranging competitively priced shipments, quality of logistics services, ability to track and trace consignments, and frequency with which shipments reach the consignee within the scheduled time, are vital to the trade flows even if countries have the common colonizers. Therefore, the results are robust to the notion that countries with common colonial ties trade more.
The SADC FTA has a negative and statistically significant coefficient at 1%, implying that the value of imports tends to reduce after the launch of the SADC FTA in 2008. Additionally, when considering the trade creation and diversion effects of the SADC FTA, there was no evidence of trade creation since the coefficients are negative and significant at 1%. On the other hand, there is strong evidence of trade diversion by the SADC FTA, resulting in the significant reduction in the value of imports after 2008.This implies that SADC countries' imports have been diverted from efficient producers to the inefficient member countries due to the reduced trade costs as a result of lowered tariffs and/or zero tariffs on various products. Whether trade diversion is welfare deteriorating for SADC countries or not, is still a debatable topic that still requires further general equilibrium research analysis that should be addressed by future research.
With regards to the governance performance effects on trade flows, the positive expected coefficients at 1% significance level, in equation 2, indicates robust evidence to support the importance of governance which is estimated using the political stability index. Therefore, improvements in the political stability of a country increases imports and exports considerably, especially exports as governance performance has a direct effect on domestic production and the costs associated with exporting. This result emphasizes the importance of governance in trade flows and the realization of the full potential of the regional arrangements like the SADC FTA. However, when additional trade costs are included, political stability, has the negative coefficient that is statistically significant at 1% for importers (PS_m) and insignificant for exporters (PS_x). This implies that countries will import less when they experience improvements in political stability, probably due to the likely increase in domestic production associated with improvements in governance.
LPI has the positive coefficients as expected and significant at 1%. Implying that improvements in LPI significantly increases both imports and exports, especially exports for all estimated equations. Therefore, logistics efficiency, of customs clearance process, quality of trade and transport related infrastructure, ease of arranging competitively priced shipments, quality of logistics services, ability to track and trace consignments, and frequency with which shipments reach the consignee within the scheduled time, is vital to the rise in trade flows in the SADC. Similarly, when this study proxied the logistical/transaction costs with the number of documents required per shipment of imports or exports, the PPML estimations show that the number of documents required for importing considerably, reduces imports when all other additional trade costs are considered, and when other costs are excluded. However, the increase in the number of documents required for exports appear to increase exports when all costs are considered and significant at 1% level. This unexpected outcome may imply that the number of documents required for exporting does not matter much to the exporters as they can cover such transaction costs through the price of exports without affecting the demand and thus, other costs are more prominent for exporters. Additionally, the global financial crisis in 2008-2009, had a negative and statistically significant effect on trade flows. This was the case probably due to the fact that South Africa and the EU28, the major exporters to SADC member countries were heavily affected by the financial crises, thus reduced the level of exports due to the volatility of the payment system during the crisis 1 .
The study also compared the PPML estimates with those of pooled OLS and fixed effects regressions and found the results to be similar with pooled OLS estimates, though PPML estimates had smaller coefficients for most variables, similar to Santos Tenreyro (2006, 2011). While the Fixed effects regeressions excluded distance, contigous, commmon colonial ties and landlockedness due to their non-variability over time, but had similar expected coefficient signs for most variables except for the SADC FTA (See Table 2 below). The fixed effects regression shows a positive SADC FTA coefficient that is statistically significacant, implying evidence of trade creation, contrary to the PPML and Pooled OLS regressions which show robust evidence of trade diverting effects of the SADC FTA. This contradictory result may be due to the excluded traditional gravity model variables that are constant over time, but vital determinants of the trade flows. The results are consistent with the recent literature that emphasize the suitability of the PPML estimation technique in constant elasticity models such as the gravity model, since it produces consistent estimates in the presence of zero trade flows and heteroscedasticity, and is more robust to truncation.  Generally, the size of the importers and exporters' economies, relative distance, contiguity, landlockedness, and logistics performance of the country pairs seem to be the major factors for the growth of the value of trade, based on the size of the coefficients, while the SADC FTA coefficient size is also considerably large enough for the negative effects on the value of trade. It is clear that the size of the economies of SADC member countries has been associated with increases in trade, although the value of imports to SADC have reduced due to the SADC FTA indicating trade diversion. Apart from the obvious direct trade costs such as tariffs, the governance and transaction related costs also significantly affects the volume of trade as indicated by the size of coefficients.
It should be stressed that the results of my regression analysis provides mainly the impact of the trade costs and the SADC FTA on the trade flows, but does not analyse the effects on production, welfare, factor returns, prices, customs revenue and dynamic variables such as changes in capital flows. This is because computable general equilibrium (CGE) models are more appropriate techniques for such variables. Plummer et al (2010) explained in detail the limitations and advantages of gravity models in comparison to CGE models. Additionally, gravity models do not account for macroeconomic convergence implications, which are important for the prospects of deep regional integration in the SADC. Macroeconomic convergence is a concept from growth theory, thus require a growth approach to analyse the implications for the SADC region. The next chapter will adress some of the limitations of the gravity model by analysing the macroeconomic convergence implications for the prospects of deep SADC regional interagtion. Future research that can analyse the effects of SADC FTA on customs revenue, prices and dynamic variables using CGE models is highly recommended.


Functional Models of Economic Propaganda in Different Political and Economic Systems – Socialism and Capitalism. Example of Selected Forms of Broadcast Advertising Messages in Poland in the Second Half of the Twentieth Century

Abstract Marketing communication in modern times is similar to the propaganda model, i.e. persuasive communication in all possible fields of exploitation. The last three decades in Central and Eastern Europe constituted a time of transformation in many areas of social, political and economic life. Thanks to immanent changes depending on the economic situation and the clash of demand and supply, it was possible to create functional models in three selected time intervals distinguished by the author (socialism, transformational period and capitalism). The use of functional models gives the opportunity to indicate how many changes have taken place in such a short period of time both in terms of consumer mentality and in satisfying the needs of producers. The basis for the application of this type of operationalization of the idea is the statement that “the functional model consists in mapping the functioning of a given system. It should give an idea of the functions and processes taking place in a given system” (Sabryła, Trzciniecki 1986). The purpose of this article is also to start a discussion on contemporary models of product communication.

Introduction. Definitions and types of propaganda
The source of the term propaganda stems from the Latin propagare, understood as "spreading", which in its original context was used strictly in a biological sense not a social one. The change in the semantics of this word, as contemporary scholars point out (including Tylor 2003: 2-7), began with the appointment by Pope Gregory XV of the Sacra Congregatio de Jarosław Kinal Propaganda Fide (Sacred Congregation for the Propagation of the Faith). The task of this commission was to "spread" the Catholic faith in countries dominated by dissenters (Praktsanis, Aronson 2008). There are two extreme approaches today in attempts to define propaganda. Some scholars refer to Jacques Driencourt, who claimed that everything is propaganda, because everything in the political and economic spheres seems to be a deliberate action aimed at achieving certain goals through media influence. In the second approach, the definition of propaganda departs from the fact that it is impossible to define its precise, scope-logical definition (Benes 2014). The literature on the subject assumes that research on the social aspects of propaganda began with the end of the First World War and was initiated by Edward Bernays, who combined the ideas of Gustav Le Bon and his work entitled Psychologie des Foules (Psychology of crowds) and the thoughts of German-speaking psychologists, among others Sigmund Freud (Ellul 1973, Laswell 1938. What is worth mentioning as an important item on the impact of propaganda on attitudes and social needs, is Harold D. Laswell's book Propaganda Techniques in the World War. Laswell attempted to explain the influence of propaganda on the attitudes of citizens during the war and outlined the basic propaganda techniques used by governments. In his propaganda concept, apart from references to behaviourism (which in the opinion of the majority of his contemporaries explained the impact of social mass media), he also referred to Freudianism. Laswellian propaganda theory refers to the phenomenon of "social fascination". In the opinion of Laswell, the effectiveness of propaganda activities contained in media messages did not result from their content or special attractiveness but from the weakness of society which, plagued by an intensifying economic and political crisis, showed increased susceptibility to this type of activity (Sporule 1997). Harold Laswell's propaganda theory is the foundation of modern thinking on propaganda understood as a multi-level action. The analysis of available English-language literature allows us to cite several basic definitions of propaganda. Bernays defined propaganda as a tool by [...] which [people] can fight for beneficial goals and help in ordering chaos (Bernays, 2005: 159). Jacques Ellul (1973: 61) considers propaganda a set of methods used by an organized group that wants to actively or passively participate in their actions as individuals ... Terence H. Qualter (after Adler 1964), points out that in propaganda [...] the message must be adapted to the specific needs of the situation and the target audience. Such an indication is important from the point of view of economic propaganda and the theory of market segmentation. Leonard Dobb and AJ Mackenzie after him, propaganda activities as an element of social engineering recognizing propaganda as an attempt to Functional models of economic propaganda in different political... influence the functioning of the impact of an unconscious or systematic action aimed at implementing certain goals and values in the social patterns, to influence other members of society with the aid of prominent leaders to accept some values as being appropriate (Welch, 2003). Karen S. Johnson-Cartee (2004), points to the fact that propaganda stands on four pillars: simplicity, addressing emotions, selection of target groups, repeatability. Oliver Thomson (1999), in his book Easily Led: A History of Propaganda, 2 distinguishes the following types of propaganda: rational, partly rationalemotional. The characteristics of these types of propaganda are presented in Figure 1.

Rational
The principle of relying on facts and the criterion of rationality and logic prevails. Tactics of propaganda activities are based on the selection of facts corresponding with its objective and omitting facts that do not serve this purpose.
Partly rational Partly rational approach to the issue dominates, while propaganda uses the allusions and similar techniques aimed at strengthening weak argumentation Emotional Is based solely on emotions and is subjective. An important element are promises and actions calculated to evoke strong emotions -hatred, fear, faith, prejudices.
Source: Own study based on Thomson (2001).
Another typology of propaganda activity is that proposed by Jaques Ellul (1973) who divides propaganda into white, grey and black. White propaganda is characterized by a well-identified sender who does not hide its origin and character and the sender's intentions and ideology are not in any way concealed, it can be assumed that white propaganda is institutionalized, and the institution that is the sender is well known. In grey propaganda, the source of information may or may not be disclosed or be commonly known. Here, true information mixes with false information and, either in whole or in part, is often imprecise. It is directed against an opponent in order to discredit him in the eyes of those receiving the message, largely by bringing into question the rival's integrity and competence. Black propaganda, also called disinformation, is portrayed as the complete opposite of white propaganda. Not only is the identity of the propagandist concealed here but so too the true characteristics of the medium. It presents nonexistent sources of information or as a source it presents an unaware person to legitimize and authenticate the facts presented. Such facts in black propaganda are false and created specifically to mislead or deceive. The success of black propaganda depends on effectively hiding its true source and the characteristics of the propagandist (Dziomdziora 2008). In the author's opinion, it is also worth proposing a division of propaganda into political, economic and social types and to consider each separately. In political propaganda, the most important goal is to obtain political power and all tools and techniques are created and implemented for this purpose. Economic propaganda adopts a less obvious form and its aim is to obtain rational and irrational benefits in the consumer relationship as well as to educate attitudes and pro-consumer values. Social propaganda uses mass media and a media apparatus to shape and model social attitudes, including creating social myths and managing collective memory. In the proposed typology, propaganda covers a wide range of forms. It can be a visual art, consisting in the transmission of bright and well-known symbols and objects, as well as photography, phonography, interactive and reactive media, as well as literature (in all forms including the distribution of leaflets), theater and cinema. In relation to a specific time segment, the author is of the opinion that propaganda and advertising should be divided. In terms of propaganda, he proposes to name this a communication act in the mass media that has an impact on the emotional sphere, building into it a sense of pride in the use of a given product or the product of a given country, region or city. In contrast, advertising can be used to determine any commercially persuasive message emitted or published in the mass media, the intention of which is to create a purchasing need or to satisfy the need for information relating to a product or its use, unique functions and/or its composition. The political concepts influencing the formation of the media ecosystem are of key importance in the concept of termination of terminological propaganda from advertising presented. In the analyzed period, one can distinguish three stages of periodization. In the first period it can be assumed that there was a propaganda phenomenon, the media ecosystem was hermetically sealed for private persuasive communication initiatives. The state authorities decided on the form and legitimacy of broadcasting. It was aimed at ideological promotion not the stimulation of consumer needs and its sole purpose was to generate mental values which, in the opinion of the authorities, would lead to positive behaviour and social attitudes. In the second -hybrid -period, the media system was opened to private factors and the intentional sphere of the message changed. Product communication assumed the nature of intentional persuasion, stimulating demand and informing about new business entities. At the same time, space was developed for the inclusion of messages generated by political institutions for the purpose of economic propaganda. The third period is characterized by the total opening up of the market and marginalization of the role of political factors in favour of private factors. The communication observed at that time is a commercial stimulation of needs and propaganda messages constitute only a small percentage of those present in the media space.

Economic propaganda as a specific type of propaganda
Among contemporary researchers of the propaganda phenomenon (e.g. Partick 2015), the main interest of mass media and media recipients from political issues to economic issues is transferred. In connection with such a thematic reorientation of the media content, reconfiguration of propaganda methods and techniques for economic matters takes place. As Krzysztof Dziomdziora (2008) points out: Economic propaganda concerns all content related to the economy or the economic system in a given country. All areas of the economy that relate directly or indirectly to entities such as interest rates, the state of foreign exchange reserves, inflation forecasts, taxation, savings, work system, etc., are appropriate for economic propaganda (Dziomdzora 2008: 17). Another researcher, H.M. Kula (2005), indicates that the main goal of economic propaganda is to create social images related to economic stability. In Kula's idea, the superiority of economic propaganda is to stop society from undertaking irrational economic activities and to create a conviction about the economic superiority of a given country. Some theoreticians of the phenomenon (Argenti 2009, Dutton, Ottermayer 1987 distinguish two types of economic communication (propaganda): state and corporate. In the first case, the goal of the state is to build a positive image internally and externally so as to acquire rational benefits for the country (increase in sales of national products, obtain lower interest rates on bonds, increased interest in the sale of debt securities) and to gain prestige (obtain membership in prestigious economic bodies, delegate its own representatives to international bodies, increase the level of participation in international certification organizations). In the second case, corporate propaganda refers to information disseminated by corporations to manipulate public opinion in relation to their business and its activities, both in terms of the internal and external market environment. The use of corporate propaganda can be widely found in the fields of advertising, marketing, politics, history (including the creation of myths) and in public relations. An inherent element of corporate propaganda is the creation and cultivation of a corporate brand.
A corporate brand is the perception of a company that links a group of products or services to the public under a common name and a common logo. The corporate branding process is about creating positive associations and a positive reputation among both internal and external stakeholders. The purpose of the corporate branding initiative is usually to hide corporate motives or improve business opportunities. (Nayyar 1990). Corporate branding is used when there is a significant degree of "information asymmetry" between the company and its clients. The phenomenon of information asymmetry is defined as a state in which customers are much less informed about the company's products than the company itself or perceive a high level of risk when buying the company's products or services, or where the brand behind the brand will be relevant to the product or service that the customer is considering to purchase (Brown, Dacin 1997). Economic propaganda at both levels affects the circulation of social and political goods in line with the flow of goods and services as presented in Figure 2. In some studies, it is proposed to identify the word economic propaganda with the word advertising, therefore, for the purposes of this article the author accepts the ideas used by George E. Belch and Michael A. Belch: (Belch 2004). Thanks to the adoption of this concept, it is possible to specify a number of types of propaganda activities with a distinction between capitalist and socialist systems as depicted in Figure 3. subliminal advertising social advertising social advertising teaser advertisement teaser advertisement information advertising information advertising reminder advertisement reminder advertisement supporting advertisement supporting advertisement company advertisement shielding advertisement targeted advertising professional advertising comparative advertising competitive advertising company advertisement aggressive advertising prestigious advertising defensive advertising Source: Author's own work.

Functional models of economic propaganda
This paper presents three models of propaganda covering three periods. The first of the discussed models concerns the situation prevalent in the 1960s, 1970s and first half of the 1980s. The second -a hybrid modelconcerns the period of transformation, i.e. from the second half of the 1980s to the mid-1990s. The third model covers the period from 1995 to the present day. The above periodization is fixed with political, economic and ideological factors in three different social spaces and in three different political systems. In the first period, the intention was to build national identity in the media and to create specific social attitudes. Here the dominant factor is political considerations. In the second period, economic factors dominated with private entities endeavouring to compete with state-owned enterprises and inform society about their products. In the third period we are dealing with the opening of the media market and the marginalization of ideological initiatives in favour of consumer promotion determined by the mechanisms of an open market economy.
The use of functional models gives the opportunity to indicate how many changes have taken place over the 30-year span of the advertising market in Poland, both in terms of consumer mentality and meeting the needs of producers. The basis for the application of this type of operationalization of the idea is the statement that the functional model consists in mapping the functioning of a given system. It should give an idea of the functions and processes taking place in a given system (Sabryła, Trzciniecki 1986). For the purposes of this study, three functional socialist, hybrid and capitalist models were distinguished. In the socialist model, the rejection of market rules is accepted. Supply being less than demand. The purpose of implementing enterprise communication is to build the image of the company (product), not information on competition. The overriding goal is to generate a positive image of the country. In this model, static visual forms such as POS and outdoor advertising are most often used. It should also be mentioned that the task of advertising at the time was not to generate profits from sales, rather it was a form of state dialogue with the public. Products were presented based on their usefulness, that is their usefulness for development. Brands were advertised despite lack of competition. Goods presented were not readily available in-store and were only planned to be made available at some time in the unidentified future. The factors shaping the advertising message were based on current ideology (party propaganda), the desire to create a social demand for goods and services ahead of their ready availability on the market (not their deficit), lack of competition between entrepreneurs, current political situation and willingness to pay the media or journalist for coverage (an informal financial support arrangement). It is important to emphasize that in this model it is not appropriate to use the synonyms recipient and consumer, because the recipient was not necessarily a consumer of the advertised goods. The main goal was to create pro-civic and pro-state attitudes and values. This model is presented in graphic form is in Figure 4. Functional models of economic propaganda in different political... In the above model, the interesting phenomenon is that it aimed to identify with the recipients of the media message not with consumers. Consequently, given the limited scope of the media and the interference of the authorities in the media messages delivered, the people to whom they were addressed had no influence on the form and content of the information the media presented to them. They were merely passive recipients of such messages. The sender, using his position in the communication process, selected and exhibited the content considered important without carrying out research on the needs of the audience. At the same time, changes in consumer methods and behaviours in the subsequent years this model functioned should also be noted. Changes in relation to specific consumption became evident in the 1970s and 1980s. The model presented only describes the broadcasting intent, leaving the media impact in subsequent time periods as a subject for further research. Of significant importance in that further research work is the phenomenon of 'role' transformation in the perception of the media message. In particular, the change of attitudes towards media content. In the initial period, in a large part of the society, the media attained considerable confidence, determined by the rationing of content and the small number of media outlets available. In the later period, in connection with the creation of the so-called "second circulation", a change occurred in the way the media was received for critical reception along with its division into official, governmental and non-official presentations.
Semantic analysis of advertising slogans allows us to draw some interesting conclusions. On the one hand, they supported monopoly companies (so in essence there was no need to create advertising campaigns anyway) and on the other hand, they promoted products imported from friendly countries. Examples of such slogans are e.g. the slogan advertising the Polish insurance company PZU "Insure your life with PZU", the promotion of watches imported from the USSR "Soviet watches -precision and perfection" or, absolutely incomprehensible from the point of view of the consumer message, "Use the services of ZURT" (a nationwide state-owned chain whose monopoly in the supply and servicing of radios, televisions and other household electrical goods was absolute). There were also advertising slogans that would be totally unacceptable in today's media, e.g. "For children and adults, healthy and ill, for breakfast, lunch and dinner delicious and nutritious dishes from eggs, poultry and poultry preserves recommend POLDRÓB". Furthermore, in the socialist model, social advertising had the task of creating appropriate attitudes and social behaviours consistent with the canon adopted in a given society. Examples of social advertising can be seen in Figures 5 and 6 below, along with an example of commercial advertising of the same period in Figure 7.  At the time of the political transformation in Poland, the factors influencing media presentation made it possible to create a hybrid model that combined the socialist model with emerging commercial needs. There was also a visible change in the orientation of shaping social attitudes towards consumer attitudes, i.e. those that stimulated purchase decisions rather than ethical attitudes. In addition, the phenomenon of intersectoral competition appeared, this related to the opening up of the market to private initiatives and rationed foreign capital. There was also a visible inspiration from the West regarding advertising, albeit at the time with limited technical capabilities. The factors shaping the propaganda message were, as new elements -demand, awareness of the existence of market competition, the influence of Western cultural patterns on local pop culture and a high level of trust in information published in the media. Thanks to such a variable advertising message, it created consumer demand and, to a limited extent, constituted a response to the needs of the population. A graphical representation of the model is shown in Figure 8.
There was also a reorientation of consumer needs from utilitarian needs, state needs for higher-order needs such as warranty, utility traits, the need to confirm prestige (Figure 9).

pl/jak-to-z-reklama-w-czasach-prl-bywalo/
From the moment the transition to the capitalist system occurred, the input factors changed yet again. Now, the factors affecting the advertising message are related to the need for consumption not to political ideology. An important factor in the creation of advertising needs is the seasonality of advertised products, e.g. advertisements for ice cream only appeared in the summer months in the PRL, whereas now they are present in the media throughout the year. An additional factor is the element of prestige and the preservation of competitive rivalry as a means to shape messages. Thanks to this approach, it became possible to create specific methods for conveying messages such as comparative advertising. The advertising message itself has to achieve the following: create emotional bonds with the client-brand line, stimulate and target consumer needs and monetize production processes (i.e. correlation of the impact of advertising on sales and the association of advertising agencies' profits, the so-called conversion factor). Graphically, this model is presented in Figure 10. In relation to the above model, one should mention the development of private media content creation companies (information agencies, advertising agencies, public relations agencies and media relations) and the change in the way the media functions, understood as a transition from the system of financing media market entities from public funds to one privately financed and driven by commercial interests and competition on the open market; which in turn led to changes in the paradigm of information quality for the paradigm of news information in the journalist's work ethic, as well as changes in the way content is exposed through both sharing and antennas for content openly or secretly sponsored by other market players.

Closing remarks
The last three decades of functioning of the PRL and the Republic of Poland became a research laboratory for those involved in marketing communication. The transition from a centrally planned economy to a free market economy was a huge challenge, not only for economists, but also for those involved in advertising. In addition, the rapid technological development of promotional tools, exemplified by video advertising originally created in the VHS standard to that currently using 4K technology, the emergence of new global forms of advertising and the adaptation of foreign advertising techniques to local needs has changed the media image, product communication and enabled the foundations for creating large national and multi-national corporations. To a large extent, it is these entities that have taken over from public and political bodies the task of promoting a positive image of the state and the nation. The functional models presented in this article are also intended to start a discussion on product communication, which discussion is not currently being carried out in a satisfactory manner.


Economic and mathematical modelling of regional market of grain crops

The article dwells upon the theoretical and applied issues of modeling grain yield at the regional level. In particular, traditional models of optimization of branch structure of the regional market of grain crops are considered, the block-diagonal economic and mathematical model of market production of grain crops is offered. The implementation of the proposed model will allow developing conceptual and methodological approaches to the definition of strategies for the development of the market of grain crops, to forecast the volume of production of grain crops in the regional context.

Introduction
Crop yield is an important generalizing indicator characterizing the level of development of agriculture in the region as a whole. In this regard, the task of improving methods of forecasting yields remains unconditionally relevant.
The yield depends on many factors, which can be divided into three groups by variability: -stable factors (location, soil mechanical composition, biological features of plants); -factors, which change from year to year occurs in one direction and has a positive impact on productivity (fertilization, reclamation, mechanization); -factors which change in time affects either positively or negatively on the formation of the crop (meteorological factors and the state of crops).
According to the criterion of time, short-term, medium-term,long term forecast. Different types of forecasts (short-term, medium-term, long-term) require different methods and approaches. For longterm yield forecasting, the method of analysis of interrelated series is used. For short-term andmedium-term forecasts it is important to investigate the influence of factors of the third group on the yield, which is set by statistical methods and is written in the form of predictive equations. Factors of the second group are taken into account as an amendment to the trend of yield growth, which is expressed by the trend line or regression equation [1,2].
It is difficult to foresee weather conditions of the planned years, therefore methods of forecasting of productivity differ in the probabilistic approach, i.e. the forecast is given with a certain probability. In this paper, we consider the prediction of yield on Markov chains, which is based on the extrapolation of trends and provides an analysis of yields on groups of plots with different yields and analysis of the probability of their transition from one group to another in the dynamics based on the transition probability matrices.
In the "Strategy of scientific and technological development of the Russian Federation", approved by the decree of the President of the Russian Federation dated December 1, 2016 № 642, it is noted that "in the next 10-15 years the priorities of scientific and technological development of the Russian Federation should be considered those areas that will allow to obtain scientific and technical results ... and provide ... the transition to a highly productive and environmentally friendly agro-and water management".
The cultivation of agricultural crops, including cereals, based on the optimization of their production management using economic and mathematical models in the region ensures the stability of highly productive crops, the preservation of fertility, prevents desiccation and will increase the level of resource conservation in conditions of differentiated sowing [3].
In this regard, the development and optimization of control parameters of production of grain crops on the basis of e modeling is an urgent problem for the effective use of water resources and stable high-yielding crops.
Traditional models for optimizing the sectoral structure of production in agro-economic systems of different levels allow to determine the need for seeds of agricultural crops, but do not take into account the varietal and reproductive composition of individual crops, while the yields of different varieties and reproductions differ significantly.
In this regard, the task of detailing the crops of grain crops in the context of varieties and reproductions in grain farms and determining the need for elite seeds and seeds of various reproductions is very important.

Materials and methods
Crop yield is an important generalizing indicator characterizing the level of development of agriculture in the region as a whole. In this regard, the task of improving methods of forecasting yields remains unconditionally relevant.
The yield depends on many factors, which can be divided into three groups by variability: -Stable factors (location, soil mechanical composition, biological features of plants); -Factors, which change from year to year occurs in one direction and has a positive impact on productivity (fertilization, reclamation, mechanization); -Factors which change in time and affect either positively or negatively on the formation of the crop (meteorological factors and the state of crops) [4,5].
According to the criterion of time, short-term, medium-term, long term forecast. Different types of forecasts (short-term, medium-term, long-term) require different methods and approaches. For longterm yield forecasting, the method of analysis of interrelated series is used [6]. For short-term and medium-term forecasts it is important to investigate the influence of factors of the third group on the yield, which is set by statistical methods and is written in the form of predictive equations. Factors of the second group are taken into account as an amendment to the trend of yield growth, which is expressed by the trend line or regression equation.
It is difficult to foresee weather conditions of the planned years, therefore methods of forecasting of productivity differ in the probabilistic approachand the forecast is given with a certain probability. In this paper, we consider the prediction of yield on Markov chains, which is based on the extrapolation of trends and provides an analysis of yields on groups of plots with different yields and analysis of the probability of their transition from one group to another in the dynamics based on the transition probability matrices [7].
We propose a block-diagonal economic and mathematical model to optimize the sectoral structure of production in specialized seed farms, supplemented by the definition of the need for elite and reproductive seeds in the context of individual varieties for grain farms in the region.
The model took into account that on the basis of science-based farming system, the share of grain in the structure of crops can vary from 50 to 60%, including winter grains -from 20 to 30 %. For unknown for each block taken the area of grain crops seeds of the super elite in the context of varieties, acreage of forage crops, livestock of farm animals [8] the regional demand for seeds of super elite varieties of different crops produced by specialized farms from the originators of varieties and determine the volume of production of elite seeds of cultivated varieties.
In a separate block, which is an aggregated commodity economy of the region, the volumes of production of seeds of grain crops and commercial grain in the context of varieties and reproductions are modeled.
The system of restrictions, as well as the system of variables, is built on blocks. The main groups of restrictions are as follows: on the use of production resources for the production and sale of products, on the implementation of agrotechnical, zootechnical and organizational and economic requirements, etc.
General requirements for all blocks and the relationship between them are implemented in the connecting block. All elite seeds produced in seed farms of the region are sold to farms that are engaged in the cultivation of reproductive seeds and commercial grain. At the same time, the restrictions of the binding unit establish a relationship between the gross collection of seeds of a particular reproduction and the possible acreage for the harvest of subsequent reproductions at the appropriate seeding rates.
These restrictions do not impose strict obligations on enterprises in terms of the full use of seed for its intended purpose, it is also assumed that part of the seeds can be sold as commercial grain.
The gross harvest of the last grown reproduction and the unused part of the sowing material of the previous reproduction is commercial grain.
Thus, as a result of solving the optimization problem for each variety and culture, the duration of their cultivation will be determined by the number of reproductions used.
As a criterion of optimality, the maximization of the amount of net income is accepted. In the structural form of economic and mathematical model can be expressed as follows.
Find the maximum value of the linear function: where xj -acreage of j-th agricultural crop of j-th type; cj -commercial products obtained from 1 hectare of sowing of j-th crop; x -the amount of production costs of the agricultural enterprise.
Provided: 1. Restriction on availability of production resources: where i -ordinal restrictions; aij -inputs of production resources of the i-th type per hectare of sowing of the j-th crop; bi -the amount of processing capacity of the i-th species available. 2. Auxiliary restriction for determination of production costs, labor costs and commodity production: where xj -required values. wherebi -size of the i-th livestock industry. 8. The area of sowing for the harvest of the next reproduction should be provided with seeds from the current crop reproduction. This restriction is contained in the binding block, which simulates the commodity economy of the region: where xjr+1 -the area of sowing for the harvest of the following reproduction; Qr -the gross grain harvest in the current reproduction; ar+1 -seeding rate of grain seeds for the harvest of future reproduction. 9. The required values: xj≥0. Thus, all conditions were recorded in mathematical form tasks to determine the optimal specialization and combination of industries in the studied elite-seed farms of the region.
One of the most important points in modelling is the preparation of reliable scientifically-based input information, from which the validity of the outcome of the decision will depend. During the preparation economic standards were used materials prepared research institutions, as well as obtained on the basis of practical activities directly in the enterprises themselves.
An important point in the development of the model is forecasting crop yields and simulation of agro-technical conditions of cultivation taking into account scientifically grounded crop rotations, resulting in the imposition of a particular culture or group of cultures limits the "bottom" and "top" depending on the agronomic requirements.

Conclusion
As a result of solving the economic and mathematical problem were determined: -Optimal parameters of functioning of specialized seed farms with determination of production volumes of eliteseeds in them; -Volumes of production of seeds of grain crops in the region in the context of varieties and reproductions; -Optimal structure of acreage in the farms of the region, producing food and feed grain, in the context of varieties and reproductions; -Volume of production of commodity grain.
Thus, the implementation of the above-mentioned model allows to develop conceptual and methodological approaches to determining the strategy of development of the market of grain crops, to forecast the volume of production of grain crops in the region in the medium term in the context of crops, varieties and reproductions, to determine the optimal parameters of production in specialized farms, to forecast the gross grain production in the region in the short term and to determine the approximate volumes of sales of elite seeds outside the region without prejudice to the domestic market.

Acknowledgments
The reported study was funded by RFBR and Volgograd region according to the research project № 19-416-343006.