Very good evening everyone. Welcome to the Hindu News Analysis brought to you by Shankara AS Academy. Here are the list of news articles chosen for discussion today. Due to technical difficulties, we were not able to publish the video yesterday. But we'll be taking some of the important articles that is relevant for the exam in today's discussion as well. Let's start today's discussion with this particular article on entry tax. See, this article has been making news for quite some time. People who are following the cinema news along with the UPSC news will know very well about this fiasco that has been happening. So this news is not very important to us from the preparation point of view. However, the entry tax is very important that we may have to know from the economics perspective. See, our country is very huge and given the size and the magnitude of our country, many goods move across its length and breadth. So the central government in order to streamline the process has put forth the proposal of entry tax in states. So what this does is, it gives the state government control over the goods which enter their boundaries. See, the entry tax is fee levied by the state governments on the transfer of goods from one state to another. And the state to which the goods are being moved levies the entry tax to protect its tax base. That is, on entry into the state, the state which is receiving the goods will levy the tax. So the entry tax is a type of indirect tax in nature, if you see. And it is levied on the shipment of goods from one state to another. And it is applicable only when goods are brought into the state for utility. And the state entry tax act of that particular state can maintain the rates for the goods of each state. And if you see the person who owns or purchases the goods at the time of entry into the state is responsible to pay the entry tax. And also, the tax rates vary for each state due to many different product categories on which the tax is imposed at different rates. And know that the enforcement of entry tax in a state falls on the department of commercial taxes of that particular state. See, the products which attract entry tax in a state depends on a lot of factors. So, it largely depends on the resource availability of the state, the needs of the state, the consumption base of the state and many others. See, the essential commodities like that of milk, sugar, rice, these things usually do not attract any entry tax. And if you see the products which are not essential for the basic living, they usually attract the entry tax, like this of the luxurious cars. Again, it varies from state to state depending on the state's policies. So, it is important to note that entry tax has been replaced recently after 2017 by the goods and services tax from 1st of July of 2017. So, under the new GST regime, the interstate movement of goods now attracts the IGST and intrastate transfers attract central GST and state GST. So, these are the important points regarding entry tax. A very similar concept is the octritex. So, what is this octritex? It is also levied by the state government like that of entry tax. But this octritex is different from entry tax in that, octritex is levied for entry of goods into one particular city limit. And entry tax is levied for entry into a state and both are levied by the state governments only. So, with that information, let us move on to the next article discussion. Our next article is based on this particular study on midday meals which is published on the Nature Communications Journal. So, what does it find is that the girls who had access to the lunches provided by the government schools through the midday meals scheme had better growth. That is, they had better height to age ratio. So, if you see in our country, stunting is a very big problem. That is, the people do not grow as much as they should in that particular age. So, this is largely an indicator of poverty or in other words, it is also an indicator of lack of nutrition especially to the girl children in a family. So, if you see generally in a family, boy children are given more preference saying he is a boy and he should eat more and he needs more energy. So, generally a girl is deprived of nutrition even at a household level. So, stunting is a social problem as well at the household level resulting in greater proportion of girls being affected by stunting. And this report is a refreshing pointer which says that midday meals has done a commendable job in combating stunting. So, the paper has found that the midday meals scheme has been associated with about 13 to 32 percentage of improvement in the height to age ratio in India between 2006 and 2016. So, in this context what we will do is let us refresh what is midday meals scheme from the exam point of view. Here is the syllabus for your reference. See, the midday meals in schools has had a long history in India. In 1925, a midday meals program was introduced for disadvantaged children in the Madras Municipal Corporation. By the middle of 1980s, three states had universalized cooked midday meal program with their own resources for children studying at the primary stage. That is, the state governments themselves took up the burden of providing the midday meals to the children without relying on the central government contributions. So, the three states were Tamil Nadu, Kerala and Gujarat. And apart from that, Union Territory of Pondicherry also did the same. And if you see by 1990-91, the number of states implementing the midday meals program with their own resources on a universal or a large scale had increased by about 12 states. And then the National Program of Nutritional Support to Primary Education that is NP-NSPE was launched as a centrally sponsored scheme in 1995. And this was aimed at enhancing the enrollment, retention and attendance and simultaneously improving the nutritional level among the children. See, how did it contribute to the enhancing of enrollment, retention and attendance? Let us understand this. See, when education was pushed towards the people, what it was, they resisted it because they wanted to send their children to work so that they will have food to eat on their plates. So, it was a question of basic survival versus education. So, obviously, the education was losing out. They didn't want their children to be educated, but they just wanted the children to live at least because they didn't have enough money to provide for their children or for themselves. So, the children were seen as a tool towards resources to earn food. They didn't send the children to the school. So, what happened was the enrollment was very less, the retention was very less and attendance was very less. So, when Midday Meals was introduced, the students were provided education as well as food which was very nutritious. So, this ended up enhancing the enrollment, enhancing the retention as well as ensuring the attendance. So, this is how Midday Meals Scheme helped in furthering the education in India. See, this Midday Meals Scheme since its launch has been repeatedly revised. Later in 2001, the Midday Meals Scheme became a cooked Midday Meals Scheme for the first time. So, under this, every child in every government and government-aided primary school was to be served a prepared Midday Meals. So, this was the status in 2001. Now, in 2007, the scheme was further revised to cover children in the upper primary classes of 6th to 8th and around 1.7 crore upper primary children were included by this expansion of this scheme. And from 2008, you see the program covers all children studying in the government, local body, government-aided primary and upper primary schools. So, you can see the list is very comprehensive, isn't it? So, it also covers the EGS, AIE Centres including the Madrasas and Makhtabas, supported by the Sarvasiksya Abhyan of all areas across the country. And most importantly, the calorific value of the Midday Meals at the upper primary stage has been fixed at a minimum of 700 calories along with 20 grams of protein. Remember this value? This can be a potential MCQ question in the preliminary. And this was done by providing 150 grams of food grains, rice or wheat per child per school day. So, this is all about the Midday Meals scheme and the progress that was achieved through the Midday Meals scheme. So, you can quote these facts in your main answers and you may also have to remember the provisions of this particular scheme for your exam. So, this brings us to the end of discussion on the Midday Meals. Okay, now our next new discussion for today is going to be based on this article about the Neglet of Sculptures. See, the news article reports about five sculptures from Khakathya era that were left under at the Neglet at the Dudaida village in Telangana's Siddhipet district. So, after a thorough survey, it was found that the five sculptures included two Devi sculptures, Chenakesava, Venugopala and Bhairava sculptures. And if you see, all of them were found to be from 13th and 14th centuries representing the Khakathya style of art. So, in this context, let us very briefly discuss about Khakathyas. See, these Khakathyas are the sub-few-day trees of the Rajshakutas and they emerged themselves as independent kings and they founded the Khakathya dynasty. And the Khakathyas were the most powerful kings of Telangana who ruled between the 12th and 13th centuries. And in these years, the kingdom became strong and they united the whole of Telugu-speaking lands. And notably, this era marked the high point in prosperity, culture and art traditions of this part of Deccan. And if you see, the Khakathya kingdom witnessed powerful kings like Ganapati Deva, Rudra Mahadevi, Prataparudra. And remember, the Khakathyas ruled from Hanumakonda in the beginning, but later they shifted their capital to Varangal. And know that the Khakathyas are well-known for their irrigation public works. And apart from that, their sculptures and fine arts are also famous. And one thing that you should remember is that the Marco Polo, the great Italian traveler, visited the Khakathya kingdom sometime during the time when Rudra Mahadevi was the ruler of the Khakathya dynasty. And he also made note of her administrative style, admiring her extensively. So, now let's talk about the architecture of Khakathyas. See, remember, the iconic Khakathya Torana is very famous. And the Pakal lake, which is very scenic, which is also famous. And the Rudreswara temple, which is also called as the Ramapa temple. And apart from that, the Thousand Pillar Temple are some of the prominent contributions of Khakathyas. See, though a major part of the temple of this period are characterized and evolved from the later Chalukyan style of temple architecture and decoration. Still, all the temples and the temple complexes of Khakathyas have a distinct style of their own as well. Exhibiting their own technology and decoration. And this has a unique place calling it the Khakathyan sculpture and architecture. So, this is all about Khakathyas. This is a brief history discussion taking a departure from the traditional current affairs. So, with that, let's move on to the next part of our discussion today. Now, let us take up this news article. See, this part of a discussion is about the draft trafficking in persons, prevention, care and rehabilitation bill 2021. Or the TIP Bill in short. See, the bill is expected to be tabled in the upcoming monsoon session of parliament. And in this context, this news article appeared in yesterday's newspaper as well. And yesterday it focused on the concerns and the criticism that surrounds the bill. And the editorial of today also focuses on the positives and the negatives of the bill. So, in this discussion, let us see the positives and the negatives of the bill. Here is the syllabus for your reference. See, literally, trafficking means dealing or trading in something illegal, alright? And trafficking in persons is called as human trafficking. See, this means the recruitment, transportation, transfer, harboring of receipt of people through forced fraud or deception. So, this is what is called as human trafficking. So, this is done with the aim of exploiting a person or people for narrow profits. So, this is a crime in India and it occurs in every region of the world. In this, men, women and children of all ages and from all backgrounds can become victims. And the perpetrators are known as traffickers who often use violence or fraudulent means and fake promises of education and job opportunities. To trick and coerce their victims. And most often this crime is committed to obtain some type of labour or some type of commercial sexual exploitation.  Alright? But human trafficking largely remains a hidden crime because the victims are transported to different countries and they face language barriers and then fear of their traffickers and the fear of law enforcement to keep victims from seeking any help. So, as we can see, the TIP is a social label and it needs to be removed from our society with zero tolerance. In this regard, a well-intended legislation of TIP Bill has been a welcome move to abolish trafficking. Alright? So, this bill is not something new in our country. Our society already has provisions which prohibits trafficking. The first and foremost is the constitution of India. So, trafficking in human beings of persons is prohibited under Article 23-1 of our constitution. So, it falls under the fundamental rights itself. That is Part 3. And apart from that, we have the Bill of the Immoral Trafficking Prevention Act of 1956 and we also have the Criminal Law Amendment Act of 2013 wherein the Section 370 of the IPC was substituted with Section 370 and 370A of IPC which provided for a comprehensive measure to counter the menace of human trafficking. Alright? And including the children. And apart from that, we have the Protection of Children from Sexual Offences Act. So, this also recognizes trafficking. And apart from that, we have specific legislations, an Act related to trafficking in women and children. This is a prohibition of Child Marriage Act, Bonded Labor System Abolition Act of 1976, the Child Labor Prohibition and Regulation Act of 1986 and we also have the Transplantation of Human Organs Act of 1994 because some people have also been trafficked to harvest their organs, right? And apart from specific sections of IPC, for example, Section 372 and 373, dealing with selling and buying of girls for the purpose of prostitution. So, apart from that, some states have also enacted specific legislations to deal with the issue. For example, Punjab. So, Punjab has the Punjab Prevention of Human Smuggling Act of 2012 to prevent the human trafficking, right? And in this long list, this bill is said to be a bright spot. So, it is to prevent the trafficking in persons, especially women and children, to counter the trafficking incidents. And it also aims to provide for care, protection and rehabilitation to the victims of trafficking while respecting their rights and creating a supportive legal, economic and a social environment for them. Then it also aims to ensure prosecution of offenders. So, let us see some of the positives of the bill. The first one is that it will apply to every offence of trafficking in persons with cross-border implications. So, this is very important because what happens is a person from India is trafficked outside the country and the police find it very difficult to nap the culprit. So, the existing legislations had the shortcoming and this legislation tries to bridge that shortcoming. So, what does this mean? That means it has a wider scope and it will include offences taking place within India and also outside India. The next is that it envisages setting up of a National Anti-Human Trafficking Committee. See, this is very important. And this committee will be set up at the national level and also at the state level. And if you see, the National Anti-Trafficking Committee will ensure overall effective implementation of the Act and which in turn will provide coordination as needed for prevention and countering these offences. And if you see, it will deal with matters related to victims such as their rescue, protection, medical care, psychological assistance, recovery, relief, rehabilitation, repatriation and reintegration. So, this aspect also tries to fill the gap that was left by the previous set of legislations. But even though it has these bright spots, author believes that the bill lacks in handling the offence of traffic. How? In a way, the author has listed all the concerns with the bill. Let us look at it. The main concern is regarding the involvement of NIA. See, as per the section 3 of the bill, NIA is the National Investigating and Coordinating Agency for these crimes. And they will be responsible for prevention and combating of the trafficking in persons and other offences as listed under the Act. See, it will also investigate, prosecute and coordinate these cases. So, it's a holistic rule, right? So, those who oppose this position of NIA argue that first, it would burden the agency further, the NIA, right? Second, it is an attack on the federalism, they say, because normally trafficking in persons cases are dealt with by the local police. And if the case is very tortuous, it is generally taken up by the CBCID, which is under the state. Now, since NIA is involved, it seems like these local enforcement agencies will not be playing any part. See, we all know the local law and order landscape is better understood by the local police, right? And diminishing their role and giving that role to a national investigating agency can prove regressive. So, that is one criticism.   Alright? So, due to this broad definition, critics argue that the bill also takes those into consideration who indulge in consensual, commercial sexual activity. That is, sex work or prostitution. So, what does this mean? This means it would criminalize sex work. That is, even if the sex workers choose the work as a profession without any external coercion, right? So, because it is consensual, it is unfair to punish these people, right? Because often sex workers are indulging in the activity due to many causative factors such as poverty, debt, lack of opportunities and others.  Here, rather than saving them from servitude, government will end up punishing them. So, further, the definition also includes pornographic acts or protection of any pornographic material as sexual exploitation. So, critics say that even the non-exploitative consensual pornographic material which is created for adult consumption will not be allowed at all. See, it has an implication on freedom of choice. Now, next criticism is that the bill aims to punish non-reporting of offenses under the Act. For example, under the Act, the commercial carriers are required to report if any person attempts to or has travelled on a commercial carrier without the identity documents or travel documents, okay? See, a commercial carrier means the one who engages in the transportation of goods or people for our commercial gains. So, they can be the drug services, they can be the travel agencies, right? So, if the commercial carrier fails to report it, they shall be punished with a fine of up to 2 lakh rupees. So, you can see how steep the fine is, right? So, at one level, it is welcome that this provision ensures that the offenses are mandatorily reported, alright? But the commercial carriers argue that most of the times the victims do not want to be reported. So, what they do is they end up travelling without valid documents, especially when they escape from these perpetrators. So, here the travel agencies, that is, the commercial carriers are being victimized, okay? In these specific circumstances. So, there is another provision in the bill, which is lauded by many, but also criticised. It is nothing but the provision of death penalty for some form of crimes. See, death penalty is another huge contentious area, which is good for another huge discussion. But here, this bill provides for death penalty and that is also very contentious. So, on a whole, the act regarding TIP is the need of the art, which is very essential because it fills a lacuna that has been left by the previous pieces of legislation. But it also needs to reconsider the contentious provisions and make them sensitive and precise. All the loose ends need to be tried up and the criticisms need to be addressed. So, this is all about the TIP Bill 2021. With that information, let's move on to the next segment of our discussion today. Now, see this article, Time to Build a Valuable Economy. So, let us take up this news article, which talks about the 1991 economic reforms and its impacts and what led to the 1991 economic crisis, right? So, as we know in 1991, India met with an economic crisis relating to the external debt. See, India was much poorer than, right? And the government was unable to make repayments on its borrowing from abroad. And India's forex reserves had dropped to levels that were not sufficient for even a fortnight. And in comparison right now, the import cover is estimated at well over 12 months. And apart from this, the crisis was further compounded by rising prices of essential goods as well then. And the origin of the India's financial crisis, if you see, can be traced from the inefficient management of the Indian economy in the 1980s itself. And the situation was so bad that even foreign exchange was spent on meeting daily consumption needs. And if you see, even then, the efforts to reduce such profligate spending on boosting exports was minimal. So, to tide over the crisis, what India did was, India approached the World Bank and the International Monetary Fund or the Bretton Woods Twins. Then, India agreed to the conditionalities of the World Bank and the IMF and announced the new economic policy. See, according to the new economic policy, it had wide-ranging economic reforms which focuses on making India more a competitive environment by removing the barriers. So, it was starkly different from what India's economic policy was before 1991. And under the new economic policy, the government initiated a variety of policies which fall under three major leads. That is the LPG reforms, which is commonly called liberalization, privatization and globalization. So, the following diagram briefly explains about the new economic policy. So, the policy reforms can be broadly classified into the structural reforms and the stabilization measures. See, the stabilization measures are the quick measures that was adopted immediately to bring effect to the short term. And the structural reforms generally brought some drastic changes which lasted for the time to come, right? And they were the privatization, liberalization and the globalization or the LPG, right? And the liberalization had the following reforms, that is deregulation, financial sector reforms, tax reforms, forex reforms and of course the trade policy reforms. Now, coming back to the op-ed, the author says that though India grew post-1991 reforms, our export sector has not changed much. For example, our huge foreign exchange reserve is the result of the huge financial inflows rather than the export surpluses. So, if you know, India almost always displays a current account deficit, whereas a capital account surplus. So, by simply reducing government control over the private sector like in the 1990s, the competitiveness cannot be established. That is, the author says more needs to be done the privatization, right? Here, the author highlights three key elements to improve a country's export competitiveness. So, they are, first, publicly provided infrastructure, which could be education or health or commercial infrastructure, like roads or railways or anything. First, second is private R&D and third is facilitating government machinery. So, this is mostly available in the case of India's software services exporters, but not for exporters of the goods, right? And this explains why India's trade in services generally has a surplus and the deficit is mostly in trade of tangible goods. So, but even almost 30 years after the economic reforms, we have failed to ensure consistently strong export performance. So, this is very much required as we cannot rely too much on the volatile portfolio capital against the balance of payment stress. And that is why the author says that the much needed reforms are yet to take place. Now, the ongoing pandemic has revealed another issue as well, the absence of certain crucial services in our country. So, our policy makers shall focus on some serious structural revisions to ensure necessary infrastructure in our country. This is apart from rebuilding our lives and the laws livelihoods will create a stable economy. So, basically this article has focused on why India's current account balance is almost always deficient and why is India import dependent and why there is a need to bring some structural changes to tilt the balance of payment in the current account in our favor, alright? So, this brings us to the end of the discussion on this particular open. Let's move on to the next segment. Next, we are taking up this news article, new quad grouping to focus on connectivity. See, this news article is from the yesterday's newspaper. So, let's look at this article in detail. So, this article is about the formation of a new quadrilateral diplomatic platform. See, know that the US, Afghanistan, Pakistan and Uzbekistan, they have agreed to form a new quad which focuses on enhancing regional connectivity. So, if you are following the news very regularly, our discussions very regularly, you will know generally quad means four countries which includes India, Australia, Japan and US. But this new quad is very different in its composition. So, remember this. See, the parties to the new quad consider long-term peace and stability in the Afghanistan as a critical factor and it also tries to enhance the regional connectivity. So, basically what it tries to do is to ensure that this particular region of three countries shall be well connected so that the trade can flourish in this region. And in order to understand the significance of this, we can recollect the recent developments of Afghanistan, right? After years of war with the Taliban, the US has been withdrawing recently. We all know that. This was a major setback for the US and if you see the Afghanistan is strategically located in the Central Asia. Look at the map and that is why it is called as the gateway to the Central Asia. So, with the formation of the new quad, what will happen is the US which is withdrawing right now will still have a hold on the Central Asian region. It will still have its presence over there and this is why this grouping is important from the US. And apart from this, the new quad group is considered as an important countermeasure to China's desire to extend its Belt and Road initiative to Afghanistan. So, have a look at this map for the better understanding, okay? Now, let us see in brief about the existing quad grouping just to, you know, differentiate the new quad and the already existing quad. See the quad officially is called as the Quadrilateral Security Dialogue and it is a strategic forum of four nations which we already saw. That is India, Australia, Japan and the US. If you see it aims to exchange the strategic intelligence and generally it has also been conducting joint military exercises as well. So, basic aim of this particular grouping is to maintain a stable balance of power in the particular region in western. And this is seen in the context of the rising security threats stemming from China. So, this quad grouping is also not new. It was first mooted in 2007. Then the former Japanese PM Shinzo Abe had put forth the idea based on the 2004 tsunami collaboration between these countries. And it was again put to forth in 2012 and then it was called as the Democratic Security Diamond. But, however, it was in 2017 the first official dialogue took place. Where did it take place? It took place in Manila. So, we can say that the quad has evolved from a loose coalition of democracy to a concrete entity. So, that met thrice since 2019 at the ministerial levels. And if you recollect the last ministerial level talk was in this February 2021. Now, we are also hearing about the possible transformation of quad into a quad plus dialogue. The idea is to convene expert discussions around shared strategic concerns among the four democracies and rotating fifth or the plus country. This would be any leading Indo-Pacific nation which could be New Zealand, South Korea and Vietnam, either one or all of these. So, this is quad plus. So, in this part of the discussion we saw about the new quad that is in the making. The existing quad which we have seen already but we have refreshed it in this discussion again. And we also saw about quad plus dialogues. So, with that let's move on to the next part of today's discussion. Now, let us take up this news article. Is Twitter acceding to take down requests? So, this is a news article from yesterday, a part of FAQ. So, let's discuss this in detail. So, this talks about the transparency report recently released by the Twitter. So, first let us know about this report and then we will see the highlights of this report. So, here is the syllabus for your reference students. So, most of the corporate giants nowadays subscribe to a practice of issuing transparency reports. And if you see the transparency reports offer companies a public facing opportunity. That is, they showcase their values and commitments to the users of their services. So, to make it simple they are just a way where the company tries to improve the public trust on them. So, in that line many corporate giants like Google, Apple, Facebook, Uber, Twitter. All of them have released such reports on a regular basis. So, with that now let's talk about the Twitter transparency report. Know that it is a biannual report. That is, it is released twice in a year by the Twitter itself. And if you see it is an initiative of Twitter in order to improve the transparency of its functioning. Basically, it tries to say that we are a transparent organization who seek the public trust. And know that the report covers sections like information requests, removal requests, copyright notices, trademark notices. And also email securities. So, the current reports which we are talking about right now is with respect to the second half of last year. That is from July 1st to December 31st of 2020. And now let us see the highlights of the latest reports of the Twitter. And some implications that we may have in our daily lives. So, one of the main sections covered by the report is the government information request. See what is this? See the government is a governing agency which is in charge of security, free speech, law and order, everything. So, we know social media plays an important role in all these aspects that we just said. So, the government at some point for security or law and order or law enforcement may seek some information from Twitter. So, that is what is called as the government information request which can be the police agency or the NIA or the raw it can be anything. So, this includes both emergency and routine legal demands for account information which are issued by law enforcement and other government agencies. See the routine legal demand from the government agencies include the subpoenas, the court orders and search warrants and others. See, here the report noted that India was the single largest source of government information request. And it says that there was about a 15% increase as well in the government information request compared with the Jan-July 2020 period. And according to Twitter, the emergency requests may be entertained if sufficient information is proving that there is an imminent threat involving danger of death or serious physical injury to a person. And Twitter says that under the category of government information requests, it did not disclose information in response to 70% of the requests. Which means of every 100 requests that the government placed, the Twitter entertained only 30% and it rejected 70% of the requests. Now secondly, the report says that India was one of the prominent sources of legal demands for removal of content. See, what is the legal demand for removal of content? See, some content that has been circulating in Twitter seems inflammatory. That is, it triggers a public outrage or it threatens the peace of a region. So government through legal sources demands the Twitter to remove all these. So that is what is called as the legal demands for removal of content. See, the legal demands provide data about the court orders and other formal demands to remove the content. And here the source of such demands can be governmental entities, lawyers representing individuals and all. And in this category, 94% of demands came from just five countries and India is one among the five. But Japan was on the top, which is followed by India at number two, followed by Russia, Turkey and South Korea. And in this regard, Twitter informed that the compliance rate in the case of requests emerging from India was far less compared with the average of the worldwide data. See, the compliance rate is nothing but the percentage of information requests where Twitter produced at least some sort of requested information. So here Twitter just says that the Twitter, the company itself did not accede to the requests of the Indian government. So that is what it means. Whereas to the other countries, say Japan or Russia or Turkey or South Korea, the Twitter was much more compliant. Now let us see the details of an India specific report of Twitter called as the India Transparency Report. So this report is published as per the provisions of the New Information Technology Intermediary Guidelines and Digital Media Ethics Code Rules 2021. And note that the rules mandated large social media companies to publish periodic compliance reports every month citing details of complaints received and the action taken there on. So according to the report, in the May-June period, the Twitter suspended over 18,000 accounts for child sexual exploitation and a further of over 4,000 accounts for the promotion of terrorism. See, these things are very good. What it implies is that when government repeatedly places requests with the Twitter, it can meet two things. One, there is a lot of content that is circulating either as fake news or inflammatory content or content that can trigger the violence in the domestic territory. That is one thing. The second thing is it can also be inferred that the government is trying to stifle free speech. It is either one of these. So in that context, this report assumes significant importance. So with that discussion, let's move on to the next segment of our discussion today. And students, there are a few articles that we have already discussed in our previous sessions. And there are three articles on that context. So the first one is pertaining to the Financial Action Task Force. So review of Financial Action Task Force on India's anti-money laundering and countering terrorist financing regime has been postponed for the second time. See, earlier it was scheduled to be held in February. Now it was scheduled to be held in September or October. But this has again been postponed due to the pandemic. So it is expected to start by September 2022 now. And the takeaway from this is about the Financial Action Task Force, which is important for the preliminary exam. We are not going to deal with it all over again. I would suggest you to look up the article from May 11th and June 26th from our discussion. And if at all you're following the discussion regularly, you all will know where is the secretariat of Financial Action Task Force is located. If you know the answer, post it in the comment section. So with that, let's move on to the next segment. This segment is about the Pegasus spyware. So very recently on July 8th of discussion, we got to know about this notorious spyware, which is called as the Pegasus. So this Pegasus spyware has made headlines because even the governments are procuring the spyware to snoop around their own people. So that is why it's very notorious and especially in the context of the surveillance states. So this Pegasus software you will be knowing from our July 8th discussion. So you can code the Pegasus software both in your essays as well as main's answer. And it can also be asked in your preliminary examination. And coming to the next article. So this is about sedition. So this article has been quite critical about the sedition provision that is in our law books. And if you recollect, we discussed this in detail in two of our earlier discussions, one in May 22nd and other one on June 4th. So both our discussions on those dates had information about sedition. And this article quotes that about 326 cases of sedition was filed between 2014 and 19. And if you see of the 326, only six have been convicted. That is about only one sixth have been convicted. So you can realize the amount of misuse this provision from our law book has been put into. So that is all about this news. You can quote this fact about 326 cases and only six people being convicted. This fact can be quoted in your answers pertaining to sedition. And that is how this article is important. So since we recently discussed sedition, a very easy question on that. What is the sedition provision that is in our law book? If you remember, post it in the comment section again. Now with that information in mind, let's move on to the last segment of today's discussion. That is practice preliminary questions. So we have three questions in that regard. Let's go over it one by one. So this first question is from the entry tax topic that we discussed in the discussion today. So we have two statements in this regard. The first one is that the union budget can make important decisions and changes in tariff structure of GST. See the first statement is wrong because see the GST council is the governing body for the implementation of GST rules in India. We all know that. And it is tasked with the duties to make important decisions and changes in the GST also. And the GST council is also authorized to determine the rate of the tax that is applicable under the GST model. The tax exemption rules, the due date or submitting GST forms, the tax related laws and the deadlines and the special exemptions for some states of India. So that is exactly why the first statement is wrong. Coming to the second statement. The GST law also provides for the creation of a consumer welfare fund wherein undue benefits made by the businesses under the GST law have to be deposited. In case it cannot be passed on to the identified recipient. See second statement is right. So with that we arrive at option B2 only. Moving on to the next question. This is again a two statement question. It is based on the Kakathya dynasty that we discussed today. So the first statement is this. Rudrama Devi was the first and only woman to rule over Andhra. And if you see the statement is correct because the ruler of Kakathya empire after the death of the father Ganapati Deva it was Rani Rudrama Devi. And if you see she was the first woman to rule over Andhra. So the first statement is correct. Now coming to the second statement. She introduced some radical changes in the administrative structure like recruiting people from non aristocratic families into the army as commanders. See this is a very valid statement and some of her notable accomplishments were also quoted by the Italian traveler Marco Polo. We saw this also in the discussion. So the right answer is option C both one and two. Now moving on to the third question. Which of the following countries share land borders with Afghanistan? We have five countries and we are asked to identify the right option. So if you see from the map Kazakhstan and Kyrgyzstan has no borders with Afghanistan. So you can see from either of the two maps. So with that we arrive at option C as the right answer where we have Uzbekistan, Turkmenistan and Tajikistan bordering Afghanistan. All right. So with that we are at the end of the practice preliminary questions section. Now here are some of the main questions inspired from our discussion today. I suggest you to write the answers and post it in the comments section for peer review. See writing few main answers every day will give you a very good edge in your main preparation. So with that let's wrap up our discussion today. If you like the video, like, share, comment and subscribe.


With barely few days to the takeoff of the new administration, the Benway State Governor Samuel Tom has inaugurated 30 units of three-bedroom bungalows built by Benway Investment and Property Company Limited BIPC in Makodi to address housing deficit faced by Nigerians and Benway people in particular. Governor Tom said estate development is important because of the high housing deficit in Nigeria and Benway State. Because of the housing deficit, we have more people who will always move housing. And so I commend you, your generous try, adding value and all your proposed initiative, not just in Benway but also in Abuja, I welcome. I have few days to leave office. The government is a continuum and BIPC have come to stay and I believe that the incoming government will also support you to ensure that you do that. The managing director of chief executive office of BIPC, Dr. Alex Te Adum, explains that the project was worth about 600 million Naira without any loan equity or grant. The estate is comprised of 30 units of three-bedroom bungalows. All rooms are as sweet. Each house sits on the minimum of about 600 square meters. We would like the Benway State government, particularly Benway State Urban Development Board, to adopt this model of one house, one economic three as part of its building plan approval regulations. Hello, hope you enjoyed the news. Please do subscribe to our YouTube channel and don't forget to hit the notification button so you get notified about fresh news updates.


Hello. Welcome to the afternoon session, the last session of this conference. My name is Gabriel Perez-Kiros and I work for the Bank of Spain. And then the first speaker that we are going to have, the keynote speaker, is going to be Jennifer Castle from Oxford University. Okay, thank you very much and let me thank the organisers for this very kind invitation and for some really fascinating talks over the past two days which have been really enjoyable. So this paper is on forecasting UK inflation. So a couple of disclaimers or apologies. First, I'm afraid it's frequentist, so that may come as a shock. Secondly, I'm afraid it's only point forecasts, so again, apologies for that. But, and thirdly, I'm afraid it's based on UK data, and of course I'm in a room full of Europeans here, but hopefully you'll see that the methodology can apply more generally. So let me start by just motivating the question. As I'm sure has been the case in Europe as well, there's been a big shock to UK inflation. We've got CPI inflation in the top panel there and CPI food inflation, and over 2022 we've had this massive rise in inflation, both in food and energy. In the UK, energy prices at the consumer level are regulated, but you can see the huge jumps over 2022. And so the interesting question is really how these big shocks to food and energy are feeding through to inflation. So the aim of this paper is to understand how the costs of energy feed through to both inflation and the broader economy. And we're going to try and produce some projections of UK inflation based on various energy scenarios. And the methods that we're going to use are to look at very long run time series of data. And the reason for doing so, I'm going to look at about 160 years of data. And the advantage of doing that is that we've got shocks like this in the past. We've had wars in the past. We've had pandemics in the past. We've had huge inflation spikes in the past. So using a long run time series of data enables us to identify the model. So I'm going to build four different models. And these are all going to be conditional models. I'm going to build models of wages, prices, unemployment and productivity. And the reason these are all separately built is that we've got quite a lot of nonlinearity feeding through. And you'll see why it's very difficult to build the whole system. But we test for super-exogeneity for each of the equations. And then we can actually put all of those equations together into a system at the end. So as I've just emphasized, the big advantage of using this long run time series of data is that we've got this past variation that we can use. But of course there's a drawback. This is going to be annual data. And that's not very helpful when one wants to forecast inflation in the current climate. And so what we're going to do is use more rapid, high-frequency data to update our forecast based on this annual projections that we're going to produce. So let me show you some of the data that we're going to model. Here we've got UK wages and prices over this 160-year period. So UK wages have risen 700-fold, prices 100-fold. So there's a huge amount of variation in the data, and that really helps with identification. And look at wages and prices, wage and price inflation. We've had periods where inflation have hit over 20% before. So that's very useful when we're looking at inflation running upwards of 10% in the current climate. As well as that, one of the key aspects over this very long time series is just how remarkably constant the cointegrating relation has been. So this is UK real wages in the red line, and the dashed blue line is UK productivity. Just look at how close they move together. That's going to provide our cointegration over this long-run time series. But I'll also note, look at the flatlining post-financial crisis. This is a real issue in the UK about the flatlining of productivity. And another interesting aspect has been what's happened to the energy use. So this is energy consumption over this long time series. So total fuel consumption is the red line, and initially it was almost all coal consumption. But then we started to diversify into gas and oil and since renewables, and now actually coal consumption is near zero. But you can see that there's been a flatlining of total fuel consumption, and that's due to big efficiencies since the 1960s. So this is the kind of data that we're going to use, the variation in that to identify contributing factors to inflation. So this is a brief route map of what I'll talk about. I'll build the conditional models of wage inflation, unemployment, productivity, and price inflation initially. And then I'll show how we combine those conditional models. But then if we want to do some forecasting, I'm going to base these forecasts on some assumptions. So we'll make some scenario projections based on higher frequency data. And then I'll give you some forecasts for 2023 and 2024 before concluding. So what's the modelling approach behind this? Well, as you've seen from this data, there's clearly non-constancy of change. This data is really highly volatile. So we're going to use a general to specific strategy, allowing for brake detection over the entire period, and allowing for non-linearities. So we're allowing for structural brakes, non-linearities, and unknown sets of variables, explanatory variables. So we're going to start by building a general unrestricted model for each of these conditional models. We'll include intercepts, lags of the dependent variables, and a huge range of conditioning variables that are all motivated by theory and past evidence. Then we'll include polynomials for possible non-linearities. And you'll see that we'll map to, say, smooth transition models using those non-linearities. We include step, impulse, and trend indicator saturation. So this allows us to detect for outliers and location shifts and trend brakes over the entire period. And then we're going to do selection, model selection. We'll retain the regressors and select for the non-linearities and the impulses at a very tight significance level. So we really have a prior that these shouldn't enter unless they're really there, if they're very significant. So we select at 0.1%. Then once we've picked up any brakes and outliers, we'll select over the regressors at a 1% significance level. And then we undertake further transformations for cointegration to include the long-run information. And then finally, we do super-exoginality testing, given the conditional single-equation conditional models. And we find that the resulting equations are congruent encompassing models. So we're content to proceed with these single-equation models. So if it's straight after lunch and you're all a bit tired and you'd like to switch off, let me give you the brief summary. This is what the four models look like. And then I'll go into some detail. But if you get this slide, then you can have a short dose. So the wage inflation model, the real wage inflation is driven by productivity and the markup, along with a really important non-linearity, which is a wage price spiral, and an additional non-linearity coming through an unemployment relation. So there's a lot of non-linearity in the wage inflation, which is really going to drive the inflation forecast. Unemployment is a remarkably simple model. Unemployment over this 160-year period is explained by real borrowing costs over revenues, which we proxy by output growth. And it fits remarkably well over this period, including the COVID period. Productivity, we model production functions. So we have labor productivity driven by capital per worker and energy per unit of capital. And we use trend breaks to capture the changes in technology. And then finally, our price inflation model depends on both short and long-term interest rates, broad money growth, commodity prices, which is really important in the current climate, world inflation and unit labor costs. So they're the four models that I'll build, and then I'll show how we combine them. So let's start with the model of real wage growth. So this model looks very complicated. I'll take you through it step by step. But the first thing to explain is we're modeling the real wage growth. That's the dependent variable here. And the first thing I want to convince you of is that it's a well-specified model. So in the top panels here, we've got the model fit and the indicator adjustment. So these are the breaks that the model picks up. We've got the scaled residuals and forecast errors, residual density and residual auto correlation function. This, for such a long time series of data, is a very nicely specified model. So we're happy that it's congruent. So what is actually going on in the model? Well, the first thing that's going on is we've got a short run impact of changes in productivity on real wages. And that's roughly about 0.5. So there's a fairly rapid incorporation of productivity increases into real wages. But notice that this is symmetric. There's no nonlinearity in that. So it also reflects the dampening of real wages due to the productivity slowdown in 2008. As well as the productivity growth, we've got this strong equilibrium correction mechanism. And you saw that in the data of real wages and productivity trending very closely together. So we've got a long run feedback to real unit labor costs of about 20%. So that's a half-life of just under four years, which is a fairly rapid incorporation. Now this coefficient is really important. This is a non-linear term reflecting a wage price spiral. So let me show you what this thing looks like. We've got, we saturated the model with polynomials and we found evidence that the Taylor expansion was a close approximation for our smooth transition model. And so we've got a smooth transition, a logistic smooth transition function in annualized squared inflation. So that's the transition variable. We select the threshold and the speed of transition by grid search and the actual data is using observed data. So the function here is this smooth transition function here. So what's going on? It's actually adjusted by a minus one. So down at the bottom here at zero inflation, this is minus one. At that point, there's very little reaction of real wages to price inflation. So workers are inattentive. They have no idea that inflation, while inflation is very low, so they ignore it and they don't make any wage demands on it. But as inflation rises, as you can see as we get up to about 10%, workers are really attentive. They realize their real wages are being eroded and so they're pushing for nominal wage rises to match price inflation. And up at this zero on the F function, that's 100% pass through. That means workers are demanding 100% compensation for the rise in inflation. So if inflation is exceeding about six to eight percent, then we should start to see wage price spirals and of course inflation at the moment in the UK is up at eight point seven percent and there's clear evidence of these second round effects through wage price spirals coming through. Now the next thing in the model is a non-linear unemployment term. So we've got unemployment. It's just demeaned over this 160-year period unemployment's roughly five percent. But the quadratic term comes in as well. So initially, well let me show you what that function looks like. So this is a non-linear unemployment function initially as the unemployment rate rises, the impact on real wages falls. That's the standard relationship that you would expect. But once unemployment hits about eight percent, now the impact on real wages actually starts to rise again. So initially we have this loss of workers bargaining power but then we get this movement along the marginal product curve which raises the real wages of those still employed both from more capital per worker and from the employed being more productive. And so actually we get this upturn in the impact on real wages. That goes to show unemployment is certainly involuntary in this world. Okay, what else do we have in the model? We've got three step shifts all around the first Second World War and these are step shifts that cannot be explained by any of the variables in the model. Okay, so these are step indicators been picked up by searching over the entire sample and they are not explained by the other variables in the model including productivity. And the sort of most realistic explanation of what's going on here is that there's been an increase in female labour force participation from the Second World War and a rapid upskilling of labour and so we get this upward shift and it's a really big upward shift. So pre-Second World War real wage growth was about 0.8% after the Second World War it jumps to 1.7% so a really big shift from the Second World War effect which needs to be modeled. Finally, we've got a step shift in 2012 this reverses unfortunately the growth that we saw post-Second World War growth shifts down by about 2% per annum and again none of the variables in the model can explain this step shift and it really is fundamental to being able to forecast over the following period. So then you might say well hang on you've got all these indicators these step shifts in the model and you're not really telling me where they're coming from the difficulty with step indicator saturation is that it's a-theoretic. We don't have a strong economic argument because we're searching for these step shifts on a data-based method and actually one way to think about this is that you can identify these step shifts or outliers, these impulses due to economic variables. So one argument might be well of course over this long time period the UK had a lot of incomes policies prices and wage controls and so can we think of the indicators as essentially picking up price and wage controls? Anyway we test for that and we find evidence that actually we can't explain the data from wage and price controls so we reject that interpretation. Then the next question is can we are we okay to model this as a conditional model because of course we've got contemporaneous variables on the right hand side and so we need to ensure we've got super exogeneity. So under the null hypothesis the parameters in that conditional model that I just showed you must be invariant to the shifts in the marginal models of any included regressors. Notice that we've got indicators step shifts already in the conditional model so you might say hang on how can you test for super exogeneity given that you've already got these step shifts. Well it's quite important to note that actually the test for super exogeneity is not impugned by the presence of common shifts in both the conditional and the marginal models. So if you've got common shifts in both the conditional and the marginal model they will stay in there and then you test for the significance of any shifts in the marginal model over and above those common shifts. And so we do that we run a var with two lags in output per worker price inflation and the unemployment rate retaining all regressors and again selecting the outliers and step shifts at a tight significance level we find 10 impulses and 7 step indicators found and then we put those into the conditional model and test for their significance and we conclude that it's valid to condition on the contemporaneous regressors in other words we have super exogeneity. So I hope you're confident that that's a good model for real wage growth. These are the forecasts and I show you these so I call them forecasts they're not really forecast they're sort of in sample model fit as it were using known regressors but the interesting thing is over the COVID pandemic crash and recovery actually the model does extremely well. So that's one model let me move on to the unemployment rate model and this is a really simple model we model unemployment as saying employment is going to increase if it's profitable to higher people and we proxy that as revenue minus costs so what are revenues well we proxy changes in revenues as changes in GDP and we've seen evidence of that through the cointegrating relation that essentially that relationship holds in terms of the costs well capital costs depend on real borrowing costs so we just look at the long-term interest rate minus inflation so combined that gives us a measure called the profits proxy and you can see in the data here that's the blue line it actually closely maps to the unemployment rate so we build a model of the unemployment rate this is the unemployment rate on lags of itself and the profits proxy we don't include non-linear terms here there's not strong evidence of non-linearity but of course we do include structural breaks and outliers and we pick those up using saturation techniques then we transform to a dynamic model in differences and we get a long run relation here of the unemployment rate essentially if the long-term interest rate equals the real growth rate then the profits proxy would be zero and equilibrium unemployment would be about 5% and that essentially matches what we see unemployment to be over this last 160 years so earlier in sample periods saw really huge key changes if you think about what's happened over 160 years we've had two world wars we've had the introduction of unemployment benefits huge industrial changes all of these things have gone on and yet this model only picks up one difference and two impulse indicators just one explanatory variable and yet this model fits very well so I think this is quite a remarkable model to try and convince you that the model fits well we've got the data the change in the unemployment rate and model fits in the blue line in the top panel there the scaled residuals, the one step ahead forecasts including COVID period residual density autocorrelalogram and the intercept adjustment you can see we just need four outliers to be corrected there so that's the second model the third model is the production function so we're going to augment the production function with energy data that's a key component of the UK data and as you can see here we've got the red line is total fuel consumption and that's consists of an energy mix that's been changing over time but also the actual total fuel consumption's flattened off since the 1960s as well and that reflects increased efficiency you can see the uptick in renewables here, the green line which is only just starting to outweigh all of the other fuels but what's quite remarkable over this long time period is that we've seen a 90% fall in the ratio of energy used to capital stock look at that huge increase in efficiency over time so that's energy per unit capital stock has really dramatically declined so how do we model this well we're going to use exactly the same methodology that I've used for the previous two models we build a dynamic model of output based on capital, labor and energy we use impulse, step and trend saturation and now notice that we're doing trend saturation as well so this allows for a broken trend in every period and that's going to be picking up changes in technology we test for homogeneity and we can impose that restriction so we end up with an equilibrium correction model of productivity, output per worker or the change in output per worker as a function of capital per worker and energy per unit of capital and that gives us a long run relation here at the bottom with the indicators capturing changes in total factor productivity again we have to test for super-exogeneity can I convince you that it's okay to model this as a single equation model so we test for the invariance of the coefficients so we model energy per unit of capital as a function of output per worker capital per worker and the lags of energy per capital select the step and trend saturation at a tight significance level and then put those into the conditional model and we find evidence of super-exogeneity so again we can use this as a single equation model we can then solve out for the long run to obtain a production function and that's our production function here sensible coefficient on labor you might think hang on that's a very high coefficient on energy compared to capital stock and I would agree I'd take the joint combination of capital and energy together but you know one can justify the coefficient on energy because essentially energy use really was crucial to the development and does the model fit well again let me convince you this is the model fit and residuals, residual density and autocorrelogram and the intercept adjustment notice we need again very few intercept adjustments so outliers but we do have one in the very last observation 2021 that's Covid going on here and notice the advantage of using saturation techniques because we can pick up outliers at the very beginning and end of the sample as well so other break detection techniques would have struggled to pick up this very last outlier and then finally the fourth model a model of price inflation so again the same methodology we're going to have a dynamic model of the GDP deflator applying saturation and selection and the variables we're going to have in our model are excess demand for output money, national debt, unemployment exchange rate, unit labor costs, interest rates, wages, world and energy prices so everything that you think matters for inflation should be in there we come up with our price inflation model note that actually it doesn't go right back to 1860 unfortunately we're still working on that because the second world war period really did have some quite big shocks to inflation that we're modeling but let me explain what's going on in the model this is the model fit and residuals residual density and autocorrelogram and actually the model fits very well so what's going on well we've got some inflation inertia so lagged inflation plays a role on the monetary side we've got the growth rate of broad money matters the change in the short term interest rate matters and the short long spread matters as well then we've got commodity price inflation that's enters in there you'll note that actually that's a tiny coefficient and in fact it's insignificant despite that we're going to keep it in because we're going to have a huge change in commodity prices to forecast and you'll see that despite the tiny coefficient on it it's actually going to play a big role in inflation forecasting as well as that we've got changes in unit labor costs and now you can start to see I've made an argument for this big nonlinearity in the real wage equation that's going to feed through unit labor costs here so the nonlinearity from that model will feed into the price inflation model then we have world inflation that also matters and we have again we've aggregated the outliers and step shifts into an index of retained indicator variables and that's mostly covering wars and previous crises then there's this interesting step shift this is we've called it the China effect so there's a step shift in 1993 and we think that represents the downward pressure in the UK from Chinese prices so let's combine those four models that was a very brief tour of four econometric models but here I've summarized them in these four equations here so notice that we modeled real wage growth but now I've just matched that nominal wage growth and this F tilde is that wage price spiral the nonlinearity that matters there everything that's exogenous is collected in these capital D terms so in those four equations there are a lot of variables in the models that were relevant and they're all picked up by these capital D terms other than what I've called endogenous variables in other words the variables from the four equation system so I'm actually going to make a simplifying assumption I'm going to close off that second nonlinearity which was the nonlinearity in unemployment if you recall the nonlinearity kicks in when unemployment rate goes above about 8% and in the UK we're well away from that at the moment so we don't need to worry about that second nonlinearity instead we need to worry more about the wage price spiral so we'll close that off and then we can just do substitution to solve out for price inflation as a function of all of the exogenous variables in those four models and we can take the coefficients from the estimated models to back out the actual parameters for this solved out price inflation model so we're going to need to make some assumptions on what the wage price spiral nonlinearity is going to be doing so I'll consider two cases to start with the first is when workers demand 100% in compensation for inflation so in other words they want nominal wages to match the price inflation the second is we'll look at when workers demand 50% of inflation as compensation so that's when F tilde is minus a half so we can then back out the parameter estimates for this solved out price inflation model and then substitute in all of the other drivers that we had the exogenous variables and this is our final conditional model for price inflation so let me talk you through what matters here so increases in the growth of broad money, energy prices, world prices the markup and the long term interest rate are all going to raise inflation and increases in capital energy in the short term interest rate all reduce inflation and so if for example if you were thinking back to 2022 when we had this energy shock if we had a reduction in energy availability of say 10% it's going to reduce output by 2.8% as you can see from production function and that would exacerbate inflation by 2% through the price inflation curve so what are the implications for current inflation well rapidly rising price inflation can stem from commodity price inflation as we've seen in there a tight labour market driving very low unemployment levels means that that second non-linearity is not going to kick in but low productivity from the recession is likely to dampen the effect of real wage growth but unfortunately the second round effects via the wage price spiral are really very significant and they can exacerbate the inflationary pressures and that's going to dominate the lack of productivity effect okay so that's the model that we're going to be looking at and I'm going to go back to the general model and so I want to forecast 2023 and 2024 but I've got more up-to-date information than just the annual data looking backwards so I'm going to come up with some assumptions for what I'll call scenario projections for inflation now when we started doing this we looked back in 2022 and really we just made some predictions and we got in a prediction for energy price inflation that's the delta P0 here of 150% so we thought energy prices would rise by 150% over 2022 it actually turned out that they rose by 170% so that wasn't a bad prediction but pretty sizable increase in energy prices so they were just based on judgment but we can do a bit better than that we can formalize the scenario sort of maybe you can call them initial conditions and to do that we'll use a technical card T so this was a method we developed in the M4 forecasting competition which is essentially a univariate statistical forecasting model and the idea of card T is that we estimate three univariate statistical forecasting models we start off by looking at a damped trend based on first differences of moving large values but we add in seasonality the second model is an autoregressive model with seasonality but we force a unit root if we're close to that and the third model is we estimate a trend halved integrated moving average model and those three models we then just take the average of those just a simple arithmetic mean and then we treat those forecasts of that average as if they were observed so we treat them as if they're part of the data rather than and then we estimate a richer autoregressive model over that forecasting period and then the fitted values from that model become our final forecast undoing any transformations that we did in the process so that's the method that we'll use to get some scenario projections for these conditioning variables so let's look at broad money we're going to need a projection of broad money over this period and this is actually very straightforward as a simple extrapolation so we're going to put in forecast of about 3% for 2023 and 2024 what about well prices well not much is going on well prices either so we put in projections of 1% and 3.5% and what about commodity prices we put in predictions of minus 34% for commodity prices long term interest rate we put in about 3.6% capital per worker unfortunately we do not have high frequency data for capital per worker so simple extrapolations of about 1.2% and energy per unit of capital is falling so that's going to be running at about minus 8% so all of those we're going to put into our assumptions and you can see these are the assumptions we've now included as the baseline assumptions for our inflation projections for 2023 and 2024 so from those we can now produce our inflation forecasts so what are our inflation well I guess these should be now cast made in 2023 given that our scenario projections were based in March 2023 so if we assume full pass-throughs that is the wage price spiral has a full impact so workers put in 100% demand for the price inflation that they've seen in that scenario we predict inflation to run at 10% and you can see the composition of that effect the rise in short-term interest rate has this very significant downward pull on price inflation but actually is counteracted by the long-term interest rate so that 10% seems actually not far from what it looks like we might be at if we had less pass-through so if the wage price spiral didn't fully kick in and workers obtained say only 50% of the inflation into their wages we would predict inflation of about 5.4% over 2023 so you can see what effect the wage price spiral has that's a really dramatic shift from 10% down to 5.4% depending on this non-linearity that's kicking in so these are the forecast for annual inflation over this period if we have full pass-through 2022 would have been about 12.5% 10% and then next in 2024 down at 7.4% much lower if the government can prevent the wage price spiral from kicking off which there's little evidence that it can do so we can actually do a bit better than that let's go back to 2022 and see how well we did and use that to try and figure out exactly how much pass-through of the wage price spiral there is so in 2022 our scenario was that there was an equally weighted rise of 50% increase in oil and 250% increase in natural gas that's what drove the 150% increase in commodity prices and you can see the commodity prices is this blue bar with a 6 on so that 6% of inflation was driven by commodity prices in 2022 out of the 12.5% so half of the rise in inflation was predicted to come through commodity price inflation short-term interest rates would need to rise to 5% to offset the direct contributions of those energy price rises and we can see the direction of which short-term interest rates are moving in now actual inflation reached 11.1% but if we look at the annualized inflation rate over 2022 it was 9% so from that actual out turn 9% we can actually reverse engineer exactly what the degree of pass-through was given known values so we can use the standardized values for 2022 for commodity prices world prices at 8.3% short-term interest rate of course short-term interest rate was rising over this time but over the year it averaged 2% long-term interest rate at 2.5% broad money growth at about 6% and given those if inflation was 9% we would have seen a pass-through of about 0.8% in other words 80% of the rising prices were demanded for in rising wages so using that estimate of 0.8% we can then look at the impact of inflation based on our scenario assumptions that we had so for an 80% pass-through we predict inflation will be 7.5% in 2023 and 5.6% in 2024 so the Bank of England are forecasting inflation of 8.3% in 2023 quarter 2 so an annualized forecast of 7.7% so we're very close to their prediction for 2023 however we're not as optimistic as they are for 2024 we're significantly higher 5.6% relative to their prediction of 3.3% so it does suggest that this degree of pass-through really, thanks, really matters it hinges on the non-linearity of the wage price spiral and there's quite a bit of evidence coming out certainly in the UK at the moment that actually wage price spirals are really starting to be embedded within the system so let me conclude there's been a recent rise in UK price inflation it was unanticipated but it certainly wasn't new by historical data and so the history can shed light on the current inflationary climate and therefore using this long run time series of data which has a lot of variation in inflation in the time period can help us to identify the explanatory factors and non-linearities so that wage price spiral would be impossible to identify if we didn't have the 1920s and 30s in our data set we also need to model structural breaks and distributional shifts and saturation techniques were really crucial to getting congruent models for these periods the conditional empirical models jointly model the dynamics location shifts, relevant variables and non-linearities here's the rub and this is where I think you're going to attack me on so the methodology doesn't produce uncertainty bands or distributional forecasts and the uncertainty that we get stems not only from model uncertainty because we've done a lot of selection and parameter estimation uncertainty but also the uncertainty from those scenario assumptions that I started with as well and so I guess my question to you today would be very helpful to have some feedback is how do you think we can embed all of those measures of uncertainty when thinking about our point forecast here but it's important to use automatic tests for super exogeneity that justifies our single equation modeling but then we combine those models to get out system forecast but you see we can't do a system model directly off because the wage price spiral in the real wage equation includes contemporaneous price inflation in a non-linear functional form so it's very hard to think about how one can do at the outset a system model so I think this is a way to justify actually getting a system by doing it in a series of single equation models finally price and wage equations combined with non-linearities can give us projections for the contributions to inflation so it's quite useful to see what the breakdown is where are the impacts coming from so despite the fact that commodity price inflation actually had a very small coefficient on price inflation model actually the sheer magnitude of the jumping commodity prices meant that it contributed half of the rise in inflation in 2022 and energy costs along with unit labor costs really do seem to be fundamental to explaining past inflation episodes and therefore are very useful for thinking about current inflationary episodes so thank you perfect timing any questions from the floor thanks thanks for the very nice presentation I guess I have two comments of really questions the first one is perhaps I missed that in the model but I was wondering if there is any role of expected inflation so inflation expectations because that's typically what workers really try to renegotiate the salaries on and then perhaps related to that I guess one could argue that if you don't increase labor costs then you kind of trigger strikes and if you live in London you see that every day every other day and so that essentially is a labor supply shock so I was wondering you know if you had a thought on the interplay between these two things increasing labor costs or vis-à-vis labor supply shocks thanks thanks a lot Jenny for this presentation so except if I missed it which may be the case you did not mention the great moderation effect right that is a fact that starting from you see what I mean Gabriel we don't have any reduction in cycles it's something that we have in most countries but it doesn't seem that you have this for the UK and the second point you did not mention something that happened in June 2016 that is a Brexit so I was wondering to what extent the Brexit can have any structural effect on exchange rate, productivity inflation and stuff like that and if you come for this in your forecast I would like to ask about the question for inflation you have also money in there do you also consider the higher order of money effect on inflation so you can trigger some spirals with this and may it be a way to model the effects of like asset purchase programs and lots of expansion of the balance sheets sorry, me first quickly it's very short your equations are a bit in the spirit of this old layered NITIL checkmen approach right and they had the price wedge as an important determinant of a price wedge spiral in there so the difference between the GDP deflator and the HIC or the CPI so I wondered about that so very nice talk, thank you I was wondering on the price equation so something that I have experienced is that when you include inflation expectations which I was missing in the equations you capture some of the nonlinearities are directly going into the inflation expectations because they are fast, I don't know here on the yearly but the capture of all the nonlinearities that you might find in the wages or in the unemployment as you were mentioning so why you didn't include inflation expectations thank you for the nice presentation about the way you present the econometric results regression results, I like very much that you also put the diagnostics there below so you know what the fit is but the R squared is almost consistently about 0.98 0.97 and that feels sort of like you think such a great fit for the single equation models and then as a time series regression person you think well maybe there's some sort of like problem with non-stationarity and I don't think that that is really the case I think it is much more because you do all the saturations that you have all these big outliers that are taking out and they of course explain a lot of the variation so you should not present the R squared without the outliers and breaks instead of the residual sum of squares or the total sum of squares that you basically account the total sum of squares with the outliers and stuff and I think more realistic I have a question myself something that worries me a little bit is the fact that fitting in sample do not mean necessarily predictive power and then I would like to suppose that there is a dummy now that is playing something that is not included in the past but you don't know if it's happening right now then perhaps something of like estimating this thing in kind of like the sample experiment saying like see with your model up to what point you will have been able to forecast future inflation and so predictive power of the sample not just fitting in sample and then just doing one exercise of the sample there are no more questions just that thank you very much for those excellent questions I hope I'll be able to address them all so let me start off with inflation expectations because there are two questions about why inflation expectations were not included so the pragmatic answer unfortunately is that we just don't have the data on it going back to 1860 and obviously it would be wonderful to include inflation expectations but over this long time period we we just don't have the data I'm less worried about not including inflation expectations because I think over 160 years it's very hard to think about how inflation expectations would have essentially been a constant effect over there I think it would have had a very variable effect over time and actually I think a lot of what the model can pick up is things that can capture inflation expectations without directly including them but I completely take the point that that is a drawback of looking at these long time series models and I think the answer would be to say let's think of it as just one model in a suite of models of which many include inflation expectations so a bit of a get out but that's my answer on inflation expectations in terms of the question about the strikes and whether we should interpret labour cost versus labour supply shocks again yes that's a very relevant point and if you look over this long run time series of data the number of periods in which there were really significant strikes in the UK versus periods in which there were significant labour cost effects and we don't disentangle the two now one might be able to argue that actually the impulse indicators could pick up the strike effect separately from the price from the labour cost effect but I'm not sure that it's actually doing that one way to test that would be to take the dates of all the strikes over the 160 year period and see how they map to the impulse indicators that we pick up but in many of the cases very few impulse indicators were picked up so I'm not sure that actually we need that but I think the point is a really good one and I think we probably need to drill down to just the real wage equation in order to try and disentangle the effect of the sort of supply side versus the cost side issue but very good point thank you very much I'll follow up on that one so the next questions are about the great moderation and the 2016 Brexit shock so the whole benefit of the impulse saturation methodology is that we can be agnostic about when shocks occur it's just whether they occur in the data so we don't impose the idea that there is a Brexit shock and in fact you'll see in the data we do not pick up a shift for Brexit and I think that's because Brexit is a massive shock to the UK economy that's undoubtable but it didn't occur in a one-off shift in fact I think it's a gradual process that's changing the entire structure of the economy and I think that's much harder to pick up so one way we could think about picking up that kind of shock is by slowly evolving shocks over time so we might think of slowly evolving trend changes that occur from the point of the Brexit referendum but actually have only started to be implemented once Brexit was actually implemented and who knows how Brexit is eventually going to be implemented so I think that's something that one probably needs to wait some time in order to disentangle the great moderation we don't pick up any big shifts and so that suggests that the great moderation those are just a reduction in volatility over time one thing you might say well we need to be modelling time-varying volatility over this period as well the diagnostics for the models suggest that our model is well behaved regardless we don't need to model time-varying volatility over this period so maybe the great moderation wasn't such a big shock in the the opposite of a shock in the UK to what one might anticipate in terms of the higher order effects of money we have a test for non-linearity so which essentially which essentially creates polynomials of all the principal components of all the regressors in the model and then we take the polynomials of these principal components the nice thing about that is that they're all orthogonal and then we test for the higher order polynomials and for the price equation actually we didn't find any evidence that they mattered and therefore we didn't go down the route of non-linear modelling and hence including polynomials of say broad money because we didn't find evidence of the non-linearity through the price equation all of the non-linearity was coming through real wages there but we did test for it but I think over this very long time series the impact of broad money is actually if you think about how central banks have been setting monetary policy over this really long time period it's very hard to see how broad money has had this constant effect over time the price wedge that was a really good point we don't have CPI data going back to 1860 unfortunately it would be lovely to include that but that's why we model the GDP deflator rather than the CPI we just don't have the data but if anyone is working on historical data and can get that for us that would be wonderful and something very important to test so again I think the argument is this just has to be one of a suite of models where one could use more recent data to look at issues like the price wedge there the R-squared really good point so I must admit I've been taught never to look at R-squared but you are right it's not an issue of non-stationarity we are essentially modelling a lot with impulses and the steps and I think you're right it's very important to exclude those particularly when you're looking at forecast confidence intervals as well because we don't want to essentially under predict the degree of certainty that we have over the forecast period by the fact that we've fitted a model fairly well by capturing the impulses and steps and so you can actually back out both the equation standard error with and without the impulses and do a comparison because if you're doing all of the work through the impulses and steps you'd worry about the model so very good point and I will correct that in future papers and then finally the predictive power out of sample yes so one of the constraints of the model that we have is of course it's based on contemporaneous data so all of our conditional models have contemporaneous variables in the conditioning model and so if we wanted to look at truly ex ante predictive power we would then need to model all of our conditioning variables as well and there's evidence that actually the more there's a forecast taxonomy that we have when we have exogenous variables that also need to be forecast that introduces a whole new layer of forecasting mistakes that one can make and so I guess that's the concern by trying to model these contemporaneous regressors in a forecasting context but that would be the true test of the model constancy indeed so I agree so I hope I've answered everyone's questions Profit margin is now very crucial issue for the Euro system there is a box also in the latest BMP report so we like to hear from you how you calculate profit margins for instance the most traditional banks use the simplistic rule the deviation from GDP at basic prices minus unit labour cost or profit which is the ratio from operational surplus over GDP thank you Yes again I'm afraid it is an issue of data constraints over this long time series because we need data in 1860 so it is purely just the markup of GDP over unit labour costs that's all, sorry


Now, question three, we want to know from you guys, do you agree that there should be a balance when it comes to using contraceptives that is both male and female? I think the contraceptives that have proven to be beneficial for the society and well-being but to Kenya there are things like P2. We have found that people who have used them excessively with the intention of maybe avoiding to be pregnant when up until later maybe in their 30s or early 40s when they attempt to, when they really want now to have the babies, they cannot. So, I think we should invest more in educating the consequences of engaging yourself in a lot of sexual behavior because when up until later contraceptives it's a little of a physical effect. Humans have that tendency to abuse. People will abuse it and then you're left to suffer the consequences of using it. I don't think there should be a balance. It's either we do away with them or we introduce them now to me. I think this is entirely by choice. It's just an independent choice you make. But I think in as much as the drug will be here with us I tend to believe men will definitely run away from it maybe because they're not so sure whether they should be using it they're not so sure of the outcome but I still think Ikuiti still matters a lot. Let it be a fair odd thing. You know the male contraceptive ones are the best because kutokawa test, see they say that the wali test narrates those things and it came out to be 99% effective. Kuliko the female ones. So, meneza se ma, the male contraceptives neza kwa better. Kuliko zamadim since they are more effective. I think it should be a balance. A 50-50 use. Maybe they use, they try if it works then I'll opt to use it the next time I use whatever we are supposed to be using. We do 50-50. This is a matter of agreement. Like you see now relationship of family because I believe this is more for family planning not maybe from my understanding not something to you see maybe they are men and women are just using maybe to over weekend or you see to avoid pregnancies but you see now with increment that's with my partner and maybe the person within marriage maybe I don't want that children that time then I will go for the same. It's all about if my partner or if my wife or my spouse is willing to take the woman if they are willing to take then there is no problem but in case then we have to balance in between of course having us agreed on that specific matter. Most of the men kumainjona meaning kurigami, kurigama meaning suena na ifa iko balanced kumadim je. Kama boy neza kwa itimike kidogo to suiva sana. kwa je saa abod iki tu nangihawiki na kontrol nangihawiki tu kontrol atwa even na pata atwa kama boy na fatu kumadim. You know these things you have to agree with your man you sit down even about having kids you have to agree siki tu tu om yon na jamulia niki chia wa atwa wei.  To my side I support it should be balanced but to some extent you see most men will be against it obvious when it come to distributing it. There should be a balance at the end of the day when a girl gets pregnant both both of you the both parties are responsible so at the end of the day last month we went to responsibility when a balance between you the male and the female and the use of contraceptives. For the longest time women have been on the receiving end of bad control or contraceptives that is the use of condoms, the injection the strips and the coil but when this vasectomy and the pill have been introduced I believe it is a time this is the right time for men to execute or be equal to us so indeed the men should actually try it and they should not be afraid of these contraceptives because they are not exposed to many dangers as opposed to the women let's head over to our fourth question and the fourth question guys here is the dilemma we want to know from you do you think that men are going to have a hard time accepting this contraceptive? you know how men behave infact those who have never went to school they will be against it and some will be against about the religions sometime you had back anything concerning those contraceptives some religion never supported so it will get those back lashes until when most of the people will have some education on it so for myself I think when it comes people should be educated about it you know Shania blank shots that is where we draw the line because you still hear them talk of I mean Mwanaume Mwanaume kama mezalisha and they cannot fire blank shots so because they are used to they are used to it's something that it's like a tradition I still think the diffusion the diffusion of that innovation you still take a long time for them to actually to actually to along the same line I cannot speak for me but I think some may advocate for it because some people maybe in the early 40s 50s or people who have families and they probably want to have something of that sort they may expose themselves to such things maybe to reduce tendencies of maybe you slept with someone and then the repercussion maybe of a pregnancy or a child they gave birth to and they are no methods of kind of clarifying if the baby is yours and stuff because DNS is not effective I already know from the internet Twitter I have a big issue so like kablawa itchukule it's a new thing so before it comes into practice it takes time but you know through convincing to advertise when you are when you are educating them and such stuff I guess it will come at a time what I accept because when you come to DEM side effects because DEM is in the future and it will be a ball in the future so it will be a ball so it will be a ball so it will be a ball in the future it will be a ball in the future they give the workipatao to in extra cost to them so they run away from the responsibilities open to maybe the challenges due to itchukule pampas ita kwa the hard time kutumia since kwa shazoia sasa ishanza kwa display it so ita kwa naeli at time since ita kwa asa all over mika tu sasa laikeni every time we are having something new maybe some people they have a different opinion about it or some mothers may use this as a skipping board maybe they want to because sometimes men are finding or human beings are finding and you cannot tell me maybe as that woman how will they trust this gentleman maybe he has actually taken these pills and they are safe maybe let us wait and see what's going to be up with this whole matter from that point but I believe it's going to be coming up with a lot of staff long scientists going to come with a lot of stuff but maybe when it comes we will see what's going to be up the whole matter I think men will have a hard time me included but at the end of the day we are looking at what are we going after the goal so come and attack kwa safe, come take kwa patam toi I think men will go for it but it will take a while well considering that you live in Africa we have a tradition, we have cultures we have beliefs in this continent now for our men they have beliefs and they have this concept that if you use a contraceptive it might put you down as a man you might start acting like a woman kuna moja mese meigo and this is all false information things have been tried and tested and of course for vaxectomy once it's done it cannot be you can't reverse it but if you decide to do it but for this new contraceptive I believe it should be tested and it should be tested immediately and once it's been tested come on men kubalini kubalitu alafu and you'll be able to save us a lot of trouble as women because you guys are not exposed to a lot of dangers unlike us just take the kubalini to kweniyo mshale run with it my name is karenjisa see you next time same place, same time