Rising risk of financial collapse for Chinese regional cities: Impacts of 1,800 trillion yen in debt (2/2)

Recently NHK News on-line reported the following:

中国の地方都市 高まる財政破綻リスク 債務1800兆円の衝撃 (2/2)

2023年11月15日 12時12分

WEB特集

(continue)

地方政府の債務 1800兆円

では、地方政府の債務はどれくらいにのぼるのでしょうか。

IMF＝国際通貨基金の試算によると、地方政府が公式に発表している債務は35兆元、日本円にすると約700兆円です。「隠れ債務」については56兆元、日本円で約1100兆円となり、合計1800兆円にものぼっています。

しかし、この金額がそれぞれの地方政府にとってどのくらいインパクトがあるのか、個別の債務がわかるデータについては、ほとんど公表されていません。

そこで私たちは、隠れ債務である融資平台の債務データをどうすれば入手できるのか、シンクタンクや大学の研究者など、複数の専門家を取材。そして、中国の民間企業がこうしたデータベースを保有していることを知り、入手しました。

まず、地方政府ごとの「債務比率」を調べました。債務比率とは、地方政府の収入に占める債務残高の割合のことで、財政の悪化状況をはかることができます。

31の省や直轄市のうち、債務の比率が最も悪い10と、最もよい10を調べた結果が下記の表です。

ワースト1位は沿岸部にある天津です。ただし債務比率が悪いのは、ほとんどが中部地域や西部地域の内陸に位置しています。これは、依然として、沿岸部と内陸側で地方政府の収入に大きな差があるためです。

例えば、中国南東の沿岸部に位置する広東省。ＩＴ産業で急速に発展を遂げた深セン※などがあり、債務の総額をみると全国6位ですが、政府の収入が多いため、債務比率にすると全国28位。債務の負担は少ないことがわかります。（※セン＝土へんに川）

一方、内陸に位置する貴州省は、債務総額約55兆円。債務比率にして667％で、ワースト4位となっています。

さらに、貴州省の債務比率の推移を見てみると、2021年から22年にかけて急速に悪化していることが分かります。じつはこの傾向は貴州省に限らず、全国的にみられました。

なぜ、急速に債務比率が悪化したのでしょうか。調べてみると、多くの地方政府の収入が、21年から22年にかけて減少していました。

大きな要因の一つが、地方政府が依存してきた「土地収入」の減少です。中国では土地は国が所有していますが、地方政府は土地の使用権を不動産開発会社に売り、その収入をインフラ開発などの財源にあててきました。

しかし、昨今の不動産会社の業績悪化に伴って、この使用権の売却収入が落ち込み、不動産業界に依存して経済を成長させてきた地方政府にとって、大きな痛手となったのです。

“財政悪化の警戒ライン” 80以上の都市

地方政府の財政状況が悪化することに、中央政府も危機感を募らせています。

中国国務院は「地方政府の債務リスクに対する緊急対応計画」という文書を発表。地方政府の債務が危機的状況にある場合、財政再建計画を開始しなければいけないとしています。

その基準については「債務の利息支払いが政府の支出の10％を超える場合」となっています。この基準は財政破綻につながりかねない、“財政悪化の警戒ライン”と考えられています。

では、中国の都市（地級市）レベルで見たとき、どれくらいの都市が警戒ラインを超えているのか。

私たちは、アメリカのシンクタンク・ロディウムグループで中国の債務問題を分析しているローガン・ライト氏に協力を依頼。利息の支払額のデータの提供を受け、分析を試みることにしました。

分析対象の利息の支払い額には、「隠れ債務」の利息も含まれています。すると、データが利用できる205の都市のうち、財政再建を必要とするレッドラインを超えているのは、87都市にのぼることがわかったのです。

ローガン・ライト氏は、最悪のシナリオも想定する必要があると、警告を鳴らします。

「今まで融資平台が発行する債券は、地方政府が“実質的に保証”していたため、安全で債務不履行となることはないと考えられてきました。しかし、実際には、一部で支払いの遅延が起きています。もし、債務不履行に陥る可能性が出てくると、債券の信用は一気に落ちてしまうでしょう。確かに、債務不履行に陥る融資平台が出てきても、2～3社くらいであれば、強引に政治の力で押さえ込むことができるかもしれません。しかし、いったんそういうことが起きれば、債務不履行の連鎖の波が押し寄せることになります」

その上で、今までのように投資に頼った成長モデルを維持することは難しいと指摘します。

建設工事が中断された道路

「融資平台を使った投資の成長モデルは、地方政府にとって自分たちの懐を痛めずに公共インフラへの投資ができるため、都合のいいものでした。しかし、もはや投資の拡大を見込むことはできません。多くの人は、中国はこれからも、政府の掲げる目標通りGDP成長率5～6％を維持できると考えているかもしれませんが、それは非常に非現実的です。中国の成長ペースは今後、鈍化していくでしょう」

データ分析から判明した「危機的状況」

中国の地方政府の財政が悪化していることは、近年多くの研究者が指摘し続けてきました。しかし、特に「隠れ債務」に関するデータは、あまり表には出てこないため、その詳細な実態が分かってきませんでした。

今回分析できたのは一部ではありますが、中国の地方財政の危機的な状況、そして、従来の投資に頼った成長モデルを変えなければ、中国経済は長期低迷につながりかねないリスクをはらんでいることが見えてきました。

このことは、中国と経済的なつながりの強い日本にとっても他人事ではなく、中国経済の動向は今後も引き続き、取材していきたいと思います。

（11月5日「NHKスペシャル」で放送）

Translation:

(continue)

Local government debt 1,800 trillion yen

So, how much debt did local governments amount to?

According to estimates by the International Monetary Fund (IMF), the officially announced debt of local governments was 35 trillion yuan, or approximately 700 trillion yen in Japanese yen. The amount of "hidden debt" was 56 trillion yuan, or approximately 1,100 trillion yen in Japanese yen, in total it would be 1,800 trillion yen.

However, about how much of an impact this amount could have on individual local government, very little data on individual debts had been made public.

Therefore, we interviewed multiple experts, including think tanks and university researchers, to find out how to obtain debt data on hidden debts in the debt platform. Then, we learned that a private company in China had such a database, so we acquired it.

First, we looked at the "debt ratio" of each local government. The debt ratio was the ratio of outstanding debt to a local government's income, and could be used to measure the deterioration of a local government's finances.

A table below showed the 10 with the worst debt ratios and the 10 with the best out of 31 provinces and municipalities.

The worst place was Tianjin, which was located on the coast. However, most of the local governments with poor debt ratios were located in the central and western regions. This was because there were still large differences in local government revenues between coastal and inland areas.

For example, Guangdong Province (広東省) was located on the southeastern coast of China. There were cities such as Shenzhen(深セン)* which had rapidly developed in the IT industry, and it ranked 6th in the nation in terms of total debt, but because of the large amount of government revenue, it ranks 28th in the nation in terms of debt ratio. You could see that the debt burden was low. [*zhen(セン) = earth river(圳)]

On the other hand, Guizhou Province, which was located inland, had a total debt of approximately 55 trillion yen. The debt ratio was 667%, ranking 4th worst.

Furthermore, looking at the trends in Guizhou Province's debt ratio, we saw that it had rapidly deteriorated from 2021 to 2022. In fact, this trend was not limited to Guizhou Province, but was seen nationwide.

Why did the debt ratio deteriorate so rapidly? When we investigated, we found that the income of many local governments decreased from 2021 to 2022.

One of the major factors was a decline in ``land revenue'' that local governments had relied on. In China, land was owned by the state, but local governments sell land use rights to real estate development companies and used the proceeds to finance infrastructure development and other projects.

However, with the recent deterioration in the performance of real estate companies, income from the sale of these usage rights declined, which had been a major blow to local governments that relied on the real estate industry to grow their economies.

More than 80 cities reached the “warning line for fiscal deterioration”

The central government was also becoming increasingly concerned about the worsening financial situation of local governments.

China's State Council released a document called ``Emergency Response Plan for Local Government Debt Risk.'' If a local government's debt was in a critical situation, a fiscal restructuring plan had to be initiated.

The yard stick was that if “it becomes that interest payments on debt exceed 10% of government expenditures''. This level would be considered a "warning line for fiscal deterioration" that could lead to financial collapse.

So, when looking at the city level (prefecture-level cities) in China, how many cities had reached and passed the warning line?

We asked Logan Wright, who analyzed China's debt problem at the American think tank Rhodium Group, to assist us. After receiving the data on interest payments, to try to do an analysis was decided.

The targeted interest payments analysis also included interest on "hidden debt." They found that of the 205 cities for which data was available, 87 cities had passed the red line requiring fiscal restructuring.

Logan Wright warned that a plan for the worst-case scenario was needed.

“Until now, the bonds issued by Loan Platform are considered to be safe and unlikely to default because they are `effectively guaranteed’ by local governments. However, delays are occurring in reality. If the possibility of default arises, the creditworthiness of the bond will drop immediately. It is true that even if defaulting loan platform appears, if there are only 2 or 3 companies, it may be possible to forcibly suppress it through political power. However, once that happens, a wave of debt defaults will surge forward.''

On top of that, he pointed out that it would be difficult to maintain the growth model that relied on investment as before.

Roads where construction work had been suspended

“The growth model of investment using financing platforms is convenient for local governments because it allows them to invest in public infrastructure without hurting their own pockets. However, we can no longer expect to see growth in investment. Many people may think that China will be able to maintain a GDP growth rate of 5-6% in line with the government's goal, but this is extremely unrealistic. China's growth pace will slow down in the future.”

“Crisis situation” revealed through data analysis

In recent years, many researchers had continued to point out that the finances of local governments in China were deteriorating. However, data on "hidden debt" in particular often had not been made public, so the detailed reality was not understood.

Although we were able to analyze only a portion of what we were able to analyze this time, there was a risk that China's local government finances were in a critical situation, and that unless the traditional investment-based growth model was changed, the risk that Chinese economy would be leading to a long-term stagnation could be seen.

Such a matter was not someone else's problem for Japan which had strong economic ties with China, and I would like to continue reporting on trends in the Chinese economy.

(Broadcast on "NHK Special" on November 5th)

              So, China is increasingly concerned about the worsening financial situation of local governments. It is found that the income of many local governments decreased from 2021 to 2022. One of the major factors is a decline in ``land revenue'' that local governments have relied on. Local governments sell land use rights to real estate development companies and use the proceeds to finance infrastructure developments. It seems that unless this investment-based growth model is changed, there is a risk that Chinese economy could head towards a long-term stagnation.

Note:

In the web-site of Rhodium Group, Logan Wright is introduced as a Partner at Rhodium Group and leads the firm’s China Markets Research work. The site further says that Logan is also a Senior Associate of the Trustee Chair in Chinese Business and Economics at the Center for Strategic and International Studies. Logan’s research focuses on China’s financial system and credit conditions in shaping outcomes within China’s economy, as well as the policies of China’s central bank. Logan and the China Markets Research team monitor China’s real economic conditions, financial market developments, and future policy directions to gauge the influence of China’s economy on global financial markets. He is also the author of three reports on China’s financial system and the country’s longer-term economic trajectory, Credit and Credibility (2018), The China Economic Risk Matrix (2020), and Grasping Shadows (2023). (https://rhg.com/team/logan-wright/)

Rising risk of financial collapse for Chinese regional cities: Impacts of 1,800 trillion yen in debt (1/2)

Recently NHK News on-line reported the following:

中国の地方都市 高まる財政破綻リスク 債務1800兆円の衝撃 (1/2)

WEB特集

2023年11月15日 12時12分

不動産大手の「恒大グループ」や「碧桂園」などが相次いで経営危機に陥り、不動産不況の波が押し寄せている中国。

経済成長が失速する中で、さらに中国経済の長期低迷を招きかねない大きなリスクが隠されていました。1800兆円を超える、地方政府の債務です。

それにより、財政破綻のリスクを抱える地方都市がいくつもあることが、NHKの独自取材で見えてきました。

（NHKスペシャル シリーズ調査報道・新世紀File1 中国“経済失速”の真実 取材班）

“財政悪化” 貴州省の実態

ことし2月、中国の貴州省政府のシンクタンクが、緊急を知らせる声明を発表しました。

「債務の問題は重大で緊急に解決すべきだが、財政が限られているため、この問題を解決するための進展が極めて難しい。自分たちだけでは、効果的に解決できないことが明らかになった」

貴州省の地方政府で、返済不可能にまで膨らんでいるという債務。一体、何が起きているのか。私たちは、中国内陸部に位置する貴州省の省都・貴陽に向かいました。

貴州省 貴陽

もともと貴州省は、中国の中でも貧しいとされてきた地域の一つでしたが、2000年以降、貧困脱却を目指す中央政府のかけ声のもとで開発が進められてきました。

その結果、この20年にわたりGDPが年平均で10％を超える成長を遂げてきたのです。

貴陽の中心部

しかし、街の郊外に出てみると、目についたのは工事が中断して放置された道路や橋、建物の数々でした。

道路ができてもあまり車が通らないため、農地の代わりに使っている農家もいました。

農家の人

「ここはまだ道路が完成していないし、車もほとんど通らない。だから唐辛子を干しているんだ。道路ができることを期待するのはやめた。道路ができても、生活が便利になるとも思えないし」

背景に「特殊な投資会社」

なぜ、このような事態に陥ってしまったのか――。

GDPを成長させるために、道路や橋などのインフラ開発を推し進めてきた貴州省。しかし、開発のための財源には限りがありました。そこで地方政府が出資して作ったのが、「地方融資平台」と呼ばれる特殊な投資会社でした。

中国の地方政府は、中央から認可された債券発行以外、資金調達が認められていません。それを回避して、資金をより集めるのが融資平台です。

銀行からの融資や債権の発行によって資金を集め、インフラ開発を推し進めてきたのです。

このスキームは、じつは中国全土の地方政府が利用してきたもので、融資平台は今では全土に1万以上あると言われています。

しかし、ここにきて、開発による収益が思うように上がらず、資金繰りが悪化する融資平台が相次いでいます。

特に、貴州省の融資平台の中には、銀行からの融資の返済が困難となり、返済を20年間繰り延べにすると公表したところも出てきているのです。

融資平台の資金繰りが悪化すれば、影響を受けるのは地方政府です。

公式の統計では、地方政府の債務の中に融資平台の債務は含まれていませんが、実際には地方政府が返済に関して保証しているとみなされているため、融資平台の債務は地方政府の「隠れ債務」と言われているのです。

(to be continued)

Translation

China was experiencing a wave of real estate recession, with major real estate companies such as Evergrande Group (恒大集團) and Biguiyuan (碧桂園)fell into financial crisis one after another.

As economic growth stalled, there were hidden major risks that could lead to a long-term slump in the Chinese economy. Local government debt exceeds 1,800 trillion yen.

As a result, NHK's own research had revealed that many local cities were at risk of financial collapse.

(NHK Special Series Investigative Reporting/New Century File 1: The Truth about China's "Economic Downturn" Reporting Team)

“Financial deterioration” actual situation in Guizhou Province

In February of this year, a think tank in China's Guizhou provincial (貴州省)government issued a statement calling for an emergency.

“The debt problem is serious and needs to be resolved urgently, but limited finances make it extremely difficult to make progress in resolving it. It has become clear that we cannot solve it effectively on our own.”

The debt of local governments in Guizhou Province had soared to the point where it was impossible to repay them. What the heck was going on? We headed to Guiyang (貴陽), the capital of Guizhou Province, located in inland China.

Guizhou - Guiyang

Originally, Guizhou Province was one of the poorest regions in China, but since 2000, development has been promoted under the guidance of the central government, which aimed to eliminate poverty.

As a result, GDP had grown at an average annual rate of over 10% over the past 20 years.

At the Heart of Guiyang

However, when I went out to the outskirts of the city, I saw many abandoned roads, bridges, and buildings due to construction stoppage.

Even after the roads were built, there were not many cars passing through it, so some farmers used it as farmland instead.

Farmer

``The roads here have not been completed yet, and there are hardly any cars passing through here. That is why I am drying chili peppers. I have stopped hoping for roads to be built. Even if roads are built, I do not think life will be any more convenient.”

“Special investment company” in the background

Why fallen into such a situation?

Guizhou Province had been promoting infrastructure development such as roads and bridges in order to grow GDP. However, financial resources for development were limited. Therefore, the local government invested and created a special investment company called ``Local Loan Platform.''

Local governments in China were not allowed to raise funds other than by issuing bonds approved by the central government. Financing in this way avoid restriction and was a platform to collect more funds.

From banks they had raised funds through loans and the issuance of bonds to promote infrastructure development.

This scheme had actually been used by local governments throughout China, and it was said that there were now more than 10,000 loan platforms across the country.

However, here we were, the profits from development had not increased as expected, and financing platforms with worsening cash flow appeared one after another.

In particular, some loans in Guizhou Province had announced that they would have difficulties in repaying loans from banks and would postpone repayments for 20 years.

If the financing platform with loan repayment worsened, it was the local governments that could be affected.

Although official statistics did not include loan-based debts in local government debt, in reality, local governments were considered to guarantee repayments, so it could be said that debts arising from loan platform were “hidden debts” of local governments.

(to be continued)

印度計劃在中國緊張局勢醞釀之際簽署台灣勞動力供應協議

Recently Yahoo News on-line reported the following:

India Plans Taiwan Labor Supply Pact While China Tensions Brew

Sudhi Ranjan Sen, Shruti Srivastava and Betty Hou

Fri, November 10, 2023 at 2:38 p.m. GMT+8

(Bloomberg) -- India is forging closer economic ties with Taiwan with a plan to send tens of thousands of workers to the island as early as next month, according to senior officials familiar with the matter, potentially angering neighbor China.

Taiwan could hire as many as 100,000 Indians to work at factories, farms and hospitals, the officials said, asking not to be identified as the discussions are private. The two sides are expected to sign an employment mobility agreement by as early as December, the people said.

Taiwan’s aging society means it needs more workers, while in India, the economy isn’t growing fast enough to create enough jobs for the millions of young people who enter the labor market every year. Taiwan is projected to become a “super aged” society by 2025 with elderly people forecast to make up for more than a fifth of the population.

However, the employment deal is likely to ramp up geopolitical tensions with China, which opposes any official exchange with Taiwan, a self-ruled island that Beijing claims as its own. China is separated from Taiwan by a narrow body of water and shares a Himalayan border with India. It’s also been India’s top source of imports for the past two decades.

A pact with Taiwan does not suggest India is discarding the “One China Policy” — a position that recognizes the island as being a part of China. However, New Delhi has not reiterated that position in public documents and has instead fostered an active unofficial relationship with Taiwan.

The India-Taiwan jobs pact is now in the final stages of negotiation, Arindam Bagchi, a spokesperson for India’s Ministry of External Affairs, told reporters on Thursday. Taiwan’s Ministry of Labor didn’t specifically comment on the India deal when contacted by Bloomberg News, but said it welcomes cooperation with countries that could provide it with workers.

A mechanism to certify the health of Indian workers willing to move to Taiwan is still being worked out, people familiar with the discussions said.

In Taiwan, where the unemployment rate dropped to the lowest levels since 2000, the government needs workers to keep the $790 billion economy going. Taiwan is offering the Indian workers pay parity with locals and insurance policies to sweeten the deal, unlike other countries that New Delhi has struck agreements with, the people said.

In India, which overtook China to become the world’s most populous country this year, the government is pushing employment pacts with developed countries facing aging workforces.

So far, India’s government has signed agreements with 13 countries, including Japan, France and the UK, and is discussing similar arrangements with the Netherlands, Greece, Denmark and Switzerland, the people said.

Ties between India and China have been tense since a border clash in 2020, the worst-ever in four decades. Both countries have moved thousands of soldiers, artillery guns and tanks to the Himalayan region since then. Diplomatic talks have made little progress with China releasing a new map in August claiming some India-controlled territories.

Three former Indian military chiefs, who stepped down last year, visited Taiwan for a security conference this year — a trip that drew objections from Beijing. Taiwan and India also have an investment promotion pact inked in 2018.

Translation

（彭博）— 據知情高級官員透露，印度正在與台灣建立更緊密的經濟聯繫，併計劃最早下個月向台灣派遣數萬名工人，這可能會激怒鄰國中國。

官員表示，台灣可以僱用多達 10 萬印度人到工廠、農場和醫院工作。由於討論是私下進行，因此要求匿名。 知情人士稱，預計雙方最早將於 12 月簽署就業流動協議。

台灣的老化社會意味著需要更多的工人，而印度的經濟成長速度不夠快，無法為每年進入勞動市場的數百萬年輕人創造足夠的就業機會。 預計到 2025 年，台灣將成為「超級老化」社會，老年人將佔總人口的五分之一以上。

然而，這項就業協議可能會加劇與中國的地緣政治緊張局勢，中國反對與台灣進行任何官方交流，台灣則是一個北京聲稱擁有主權的自治島嶼。 中國與台灣僅一水之隔，與印度接壤喜馬拉雅山。 過去二十年來，它也是印度最大的進口來源。

與台灣達成協議並不意味著印度放棄「一個中國政策」 - 這項政策承認台灣是中國的一部分。 然而，新德里並未在公開文件中重申這一立場，而是與台灣建立了積極的非官方關係。

印度外交部發言人 Arindam Bagchi 週四對記者表示，印度與台灣的就業協議目前正處於談判的最後階段。 在接受彭博新聞社採訪時，台灣勞工部沒有具體評論印度協議，但表示歡迎與能夠向其提供工人的國家合作。

知情人士稱，一項用於證明願意前往台灣的印度工人健康狀況的機制仍在製定中。

在台灣，失業率降至 2000 年以來的最低水平，政府需要工人來維持 7,900 億美元的經濟運作。 知情人士稱，台灣向印度工人提供與當地人同等的工資和保險政策，以增加交易的吸引力，這與新德里其他國家已達成的協議不同。

印度今年超越中國成為世界上人口最多的國家，政府正在推動與面臨勞動力老化問題的已開發國家簽訂就業協議。

知情人士稱，到目前為止，印度政府已與日本、法國和英國等 13 個國家簽署了協議，並正在與荷蘭、希臘、丹麥和瑞士討論類似的安排。

自2020年發生四十年來最嚴重的邊境衝突以來，印度和中國之間的關係一直緊張。 此後，兩國已向喜馬拉雅地區派遣了數千名士兵、大砲和坦克。 外交談判幾乎沒有任何進展，中國八月發布了一份新地圖，聲稱對一些印度控制的領土擁有主權。

去年卸任的三名前印度軍事首長今年訪問台灣參加安全會議，但這次訪問遭到了北京的反對。 台灣和印度也於 2018 年簽署了投資促進協議。

So, India is developing closer economic ties with Taiwan with a plan to send tens of thousands of workers to the island that would potentially anger China. Taiwan may hire as many as 100,000 Indians to work at factories, farms, and hospitals. In the eyes of China, India probably is a trouble maker.

Developing countries' debt to China is at least 166 trillion yen; many countries face financial difficulties as repayment deadline approaches

Recently CNN.co.jp reported the following:

途上国の対中債務、少なくとも１６６兆円　返済期限迎えるも多くの国が財政難

2023.11.10 Fri posted at 18:00 JST

香港（ＣＮＮ） 途上国各国が中国の金融機関に対して抱える債務が少なくとも１兆１０００億ドル（約１６６兆円）に膨れ上がっていることが、最近公表されたデータ分析の結果から明らかになった。中国が過去２０年間にわたり行ったこれらの貸し付け数千件のうち、半数以上は返済期限を迎えているが、借り手となっている国々の多くは財政的な苦境に追い込まれている。

米バージニア州にあるウィリアム・アンド・メアリー大学の研究機関、エイドデータによると、中国の金融機関に対する期限経過貸付金の返済は急増している。分析の結果、中国の発展途上世界向けの債権額のうち８割近くは、現在財政難にある国々の支援に振り向けられているという。

長年、中国政府は自国の財政を組織して、貧困国のインフラ開発の資金に充ててきた。こうした取り組みの一つである巨大経済圏構想「一帯一路」は今秋、発足から１０年を迎える。

こうした資金は各国の道路や空港、鉄道、発電所の建設に使われ、債務国側の経済成長を助けた。多くの国々の政府と中国政府との関係は深まり、同国は世界最大の債権国となった。一方で、無責任な貸し付けが行われているとする非難の声も噴出している。

エイドデータは過去２０年以上にわたり中国が１６５カ国に行った貸し付けに関する分析を公表。それによれば現在そうした貸し付けの５５％が返済期間に入っているという。

エイドデータを統括し、今回の報告も執筆したブラッド・パークス氏はＣＮＮの取材に答え、これらの貸し付けの多くは一帯一路の構想以降に行われたものだと説明。それぞれの貸し付けに設けられた５～７年の返済猶予期間は新型コロナのパンデミック（世界的大流行）で２年間延長されもしたが、ここへ来て状況は変わりつつあるという。過去１０年ほどの間世界最大の債権国だった中国は、今や事実上、世界最大の債権回収国になっているというのがパークス氏の見立てだ。

エイドデータが依拠するデータは、中国政府及び国有の金融機関が低中所得国向けに２０００～２１年にかけて貸し出した資金に関するものであり、その総額は１兆３４００億ドル。中国の財政活動は不透明なことで知られるが、これらのデータは個々の貸し付けや補助金にまつわる公式情報の収集を通じて作成した。

研究者らはこの他、貸し手側がスイスにある国際決済銀行（ＢＩＳ）に報告したデータも引用している。これによると途上国が中国に負っている債務は、２１年の時点で１兆１０００億～１兆５０００億ドルに上ることが示唆される。

エイドデータによれば、中国から途上国への財政支援はパンデミックの始まりに伴って減少した。１６年に１５００億ドル近くのピークに達していたこれらの金額は、２０年には１４年以来の低水準となる１０００億ドル未満に落ち込んだ。

ただ貸し付け自体は依然として数百億ドル規模の水準にあることが、エイドデータの直近のデータからうかがえる。２１年の支援は補助金と貸し付けを含めて７９０億ドルと、前年から５０億ドル増加した。

一方、世界銀行が２１年に行った財政支援の総額は５３００万ドル前後だった。

Translation

Hong Kong (CNN) The debt owed by developing countries to Chinese financial institutions had ballooned to at least $1.1 trillion (approximately 166 trillion yen), a recently released data analysis revealed. More than half of the thousands of loans China made over the past two decades were now due, forcing many countries that had made borrowing into financial trouble.

According to AidData, a research institute at the College of William and Mary in Virginia, repayments of loans over time to Chinese financial institutions had skyrocketed. Analysis showed that nearly 80% of China's debt to the developing world was being allocated to aid countries currently in financial distress.

For years, the Chinese government had organized its finances to support infrastructure development in poor countries. One of these initiatives was the mega-economic zone concept “One Belt, One Road” and this fall marked the 10th anniversary of the launch of such an initiative.

These funds were used to build roads, airports, railways, and power plants in individual country, helping the debtor countries to grow their economies. Relations between many countries' governments and the Chinese government deepened, and China became the world's largest creditor nation. On the other hand, there were also voices of criticism that irresponsible lending was being carried out.

AidData published an analysis of China's loans to 165 countries over the past 20 years. According to the report, 55% of such loans were currently in the repayment period.

Brad Parks, who oversaw AidData and also wrote this report, told CNN that many of these loans were made after the Belt and Road Initiative. The five-to seven-year repayment grace period for each loan was extended by two years due to the coronavirus pandemic (world pandemic), but now came the situation that things were starting to change. Parks believed that China, which had been the world's largest creditor country for the past decade or so, now effectively became the world's largest debt collector.

AidData, relying on data related to funds lent by the Chinese government and state-owned financial institutions to low- and middle-income countries between 2000 and 2021, found the amount was totaling $1.34 trillion. Although China's fiscal activities were notoriously opaque, these data were generated by collecting official information on individual loans and subsidies.

The researchers also cited data reported by lenders to the Bank for International Settlements (BIS) in Switzerland. This suggested that the debt owed by developing countries to China could reach between $1.1 trillion and $1.5 trillion in 2021.

According to AidData, financial support from China to developing countries declined with the onset of the pandemic. These amounts, which peaked at nearly $150 billion in 2016, fell to less than $100 billion in 2020, the lowest level since 2014.

However, the latest data from AidData showed that lending itself was still at a level in the tens of billions of dollars. In 2021, aid totaled $79 billion, including grants and loans, an increase of $5 billion from the previous year.

Meanwhile, the total financial support provided by the World Bank in 2021 was around $53 million.

              So, although China's fiscal activities are notoriously opaque, AidData relying on open data works out the amount of debt owed by developing countries to China and shows that it could reach between $1.1 trillion and $1.5 trillion in 2021. According to an expert, China has now effectively become the world's largest debt collector. Probably China needs this money to deal with its internal economic difficulties.

Note:

1. AidData, with Brad Parks as the Project Leader, is a research lab based at W&M's Global Research Institute. AidData claims that it equips policymakers and practitioners with better evidence to improve how sustainable development investments are targeted, monitored, and evaluated. Their research serves the unique needs of both the policy and academic communities, as well as acting as a bridge between the two. (https://www.wm.edu/offices/global-research/research-labs/aiddata)

2. College of William & Mary, located in Williamsburg, Virginia, is the second oldest college in the U.S. The university has more than 30 undergraduate programs and more than 10 graduate and professional degree programs. (https://www.wm.edu/)

貨幣價格上漲，不僅是因為美國聯儲局(2/2)

Recently Yahoo News on-line reported the following:

The Price of Money Is Going Up, and It’s Not Only Because of the Fed (2/2)

Jamie Rush, Martin Ademmer, Maeva Cousin and Tom Orlik

Mon, November 6, 2023 at 8:00 a.m. GMT+8

(continue)

All that is changing. Some of the forces that drove the price of money lower are swinging into reverse. And other vectors are coming into play.

Demographics are shifting. The baby boom generation that helped push borrowing costs down is exiting the workforce—resulting in a smaller supply of savings. Fracturing relations between Washington and Beijing, and a rebalancing of China’s economy, mean the flow of Chinese savings across the Pacific into Treasuries has come to an end.

US debt leaped as the global financial crisis ripped through the economy and again as the coronavirus pandemic struck. Those episodes increased competition for savings, and the government has kept the taps open with the Inflation Reduction Act. Rising debt is already creating upward pressure on long-term borrowing costs.

How much higher will the natural rate go? Our model shows a rise of about a percentage point from a trough of 1.7% in the mid-2010s to 2.7% by 2050. In nominal terms, that means 10-year Treasury yields could settle somewhere between 4.5% and 5%. And the risks are skewed toward even higher borrowing costs than our baseline suggests.

If the government doesn’t get its finances in order, fiscal deficits will stay wide. The fight against climate change will require massive investment. BloombergNEF estimates getting the energy network in shape to achieve net-zero carbon emissions will cost $30 trillion. And leaps forward in artificial intelligence and other technologies might yet boost productivity—resulting in faster trend growth.

High government borrowing, more spending to fight climate change, and faster growth would all drive the natural rate higher. According to our estimates, the combined impact would push the natural rate to 4%, translating to a nominal 10-year bond yield of about 6%.

Even in our baseline projection, the shift from a falling to a rising natural rate will have profound consequences for the US economy and financial system. Since the early 1980s, house prices in the US have roared higher, with the decline in interest rates a major contributing factor. With borrowing costs now set to edge higher, that process may come to an end. There’s a similar story in equity markets. Since the early ’80s, the S&P 500 has surged upward, powered in part by lower rates. With borrowing costs on the rise, that impetus for ever-increasing equity valuations will be taken away.

Perhaps the biggest loser, though, will be the US Department of the Treasury. Even if debt rose no further relative to the size of the economy, higher borrowing costs are set to add 2% of GDP to debt payments annually by 2030. If that had been the case last year, the Treasury would have paid out an extra $550 billion to bondholders, which is more than 10 times the amount of security assistance the US has funneled to Ukraine so far.

Of course, higher rates create winners as well as losers. Savers with their money in bank accounts will get higher returns, and those piling into bonds will get a better rate of return. And a higher natural rate would also mean that—when recessions hit—there will be a little more room in the yield curve for the Fed to squeeze borrowing costs and stimulate growth, restoring some of monetary policy’s lost firepower. After years of falling rates, though, the US—and the world—needs to brace for a reversal. For everyone from homeowners to 401(k) equity investors to the US Treasury, that’s going to be a wrenching transition.

The model we use to estimate the natural rate is a vector autoregressive model (VAR) with common trends. It’s similar in spirit to Del Negro et al. (2017) and Del Negro et al. (2019) and is estimated from 1Q 1968 to 4Q 2022 with spillovers between 12 advanced economies. Our model is underpinned by three main beliefs: that the natural rate is determined by fundamental economic drivers, that actual borrowing costs will eventually return to the natural rate over time, and that survey data contain useful information about where the natural rate may lie. The VAR model and the survey data are only used to sharpen our estimates of the relationships between the drivers and the natural rate. To project the natural rate forward, all we need is projections of the drivers—these forecasts are drawn from the wider Bloomberg Economics team. Much of the literature on the natural rate focuses on short-term interest rates. We focus on long-term rates because central banks have increasingly relied on lowering them to support the economy, and because the 10-year Treasury bond yield is a crucial benchmark in global markets.

Translation

（繼續）

一切都在改變。 一些推動貨幣價格下跌的力量正在逆轉。 其他可變力量也開始發揮作用。

人口結構正在改變。 幫助降低借貸成本的嬰兒潮世代正在退出勞動市場，導致儲蓄供應減少。 華盛頓和北京之間關係的破裂以及中國經濟的再平衡，意味著跨越太平洋流入美國國債的中國儲蓄情況已經結束。

隨著全球金融危機席捲經濟，美國債務激增，及隨著冠狀病毒大流行的爆發，美國債又務再次飆升。 這些事件加劇了爭儲蓄競爭，政府因《通貨膨脹削減法案》保持了開放。 債務上升已經給長期借貸成本帶來了上行壓力。

自然利率會高出多少？ 我們的模型顯示，到2050 年，這增長率是約1.0%, 從2010 年代中期1.7% 的低谷上升到2.7% 左右。表面上，這意味著10 年期債卷的利率可能穩定在4.5% 至5%之間。 而且風險是偏向比我們的基準顯示的更高的借貸成本。

如果政府不把財政整頓，財政赤字將繼續擴大。 應對氣候變遷需要大量投資。 彭博新能源財經 估計，建立能源網路以實現淨零碳排放將花費 30 兆美元。 人工智慧和其他技術的飛躍可能會提高生產力，從而帶來更快的成長趨勢。

龐大的政府債務、應對氣候變化的更多支出, 以及更快的成長都將推高自然利率。 根據我們的估計，綜合影響將使自然利率升至 4%，相當於 10 年期債券名義上的利率約為 6%。

即使我們以基準線去預測，自然利率從下降到上升的轉變也將對美國經濟和金融體系產生深遠的影響。 自1980年代初以來，美國房價一路飆升，其中利率下降是主要推動因素。 隨著借貸成本現在逐漸上升，這個過程可能會結束。 股票市場也有類似的故事。 自 80 年代初以來，標準普爾 500 指數一路飆升，部分原因是利率下降。 隨著借貸成本上升，股票估值不斷上升的動力將被消除。

不過，也許最大的輸家將是美國財政部。 即使債務相對於經濟規模不再進一步增加，到 2030 年，較高的借貸成本也將導致債務支付每年增加 GDP 的 2%。如果去年是這種情況，財政部將要額外支付 5,500 億美元美元給債券持有人, 這是美國迄今向烏克蘭提供的安全援助金額的十倍以上。

當然，較高的利率會產生贏家，也會產生輸家。 將錢存入銀行帳戶的儲戶將獲得更高的回報，而將資金投入債券的人仕將獲得更高的回報率。 更高的自然利率也意味著，當經濟衰退來襲時，聯儲局在收益率曲線上將有更多的空間來壓縮借貸成本並刺激成長，從而恢復貨幣政策所失去的部分火力。 不過，經過多年的利率下降，美國乃至世界需要做好面對逆轉的準備。 對於從房屋主人到 401(k) 股權投資者再到美國財政部的每個人來說，這都將是一個痛苦的轉變。

我們用來估計自然率的模型是具有共同趨勢的向量自我迴歸模型（VAR）。 它在精神上與Del Negro等人（2017）和及Del Negro等人（2019）相似，估算時間為 1968 年第一季至 2022 年第四季度，涉及 12 個已開發經濟體之間的溢出效應。 我們的模型以三個主要信念為基礎：自然利率由基本經濟驅動因素決定，隨著時間的推移實際借貸成本最終將回歸自然利率，及調查數據藏有有關自然利率可能所在位置的有用資訊。 VAR 模型和調查數據僅用於加強我們對驅動因素與自然利率之間關係的估計。 為了預測自然利率，我們所需要的只是對驅動經濟的因素的預測 - 這些預測來自更廣泛的彭博經濟團隊。 許多有關自然利率的文獻都只關注短期利率。 我們關注長期利率是因為央行越來越依賴降低利率來支持經濟，而十年期美債券利率是全球市場的重要基準。

              So, the price of money—like the price of anything else—reflects the balance of supply and demand. Higher supply of saving pushes rates down. More investment demand pushes them up. The low interest period is now reversing. Bloomberg’s dataset shows that in the 1960s and ’70s, a swelling workforce and rapid productivity gains meant average annual growth of gross domestic product was close to 4%. Strong growth created a powerful incentive to invest—lifting the price of money. By the 2000s those drivers were running out of steam. After the global financial crisis of 2007-08, average annual GDP growth slumped to around 2%. A more sluggish economy meant the attractiveness of investing for the future was weaker—dragging the price of money lower. About the future, I am wondering how the current high interest situation will affect the US that has a huge national debt.

Note:

a. A yield curve (收益率曲線)is a line that plots yields, or interest rates, of bonds that have equal credit quality but differing maturity dates. The slope of the yield curve can predict future interest rate changes and economic activity. There are three main yield curve shapes: normal upward-sloping curve, inverted downward-sloping curve, and flat. (https://www.investopedia.com/terms/y/yieldcurve.asp)

b. Vector autoregression (VAR) (向量自我迴歸模型)is a statistical model used to capture the relationship between multiple quantities as they change over time. VAR models generalize the single-variable (univariate) autoregressive model by allowing for multivariate time series. VAR models are often used in economics and the natural sciences. VAR models do not require as much knowledge about the forces influencing a variable as do structural models with simultaneous equations. The only prior knowledge required is a list of variables which can be hypothesized to affect each other over time. (Wikipedia)

貨幣價格上漲，不僅是因為美國聯儲局 (1/2)

Recently Yahoo News on-line reported the following:

The Price of Money Is Going Up, and It’s Not Only Because of the Fed (1/2)

Jamie Rush, Martin Ademmer, Maeva Cousin and Tom Orlik

Mon, November 6, 2023 at 8:00 a.m. GMT+8

(Bloomberg) -- What’s the most important price in the global economy? The price of oil? The price of semiconductors? The price of a Big Mac? More important than any of these is the price of money. For more than three decades it was falling. Now it’s going up. Ask most people how the price of money is set, and they’ll say central banks. True, when it comes to direct control of US interest rates, the Federal Reserve calls the shots. But there’s a deeper logic at work. Fundamentally, the price of money—like the price of anything else—reflects the balance of supply and demand. Higher supply of saving pushes rates down. More investment demand pushes them up.

For the economics wonks, the price of money that balances saving and investment while keeping inflation stable has another name: the “natural rate of interest.” To see why this concept is central to policymaking, imagine what would happen if the Fed set borrowing costs well below the natural rate. With money too cheap, there would be too much investment, not enough saving, and the economy would overheat—resulting in spiraling inflation. Flipping that around, if the Fed set borrowing costs above the natural rate, there would be too much saving, not enough investment, and the economy would cool—resulting in rising unemployment.

For more than three decades, borrowing costs in the US were trending down. By our estimates, and adjusting for inflation, the natural rate of interest for 10-year US government bonds fell from a bit more than 5% in 1980 to a little less than 2% over the past decade.

To find out what drove interest rates lower, and to forecast where the natural rate might go in the future, we built a model of the big factors driving the supply of saving and demand for investment. Our dataset spans a half-century and 12 advanced economies deeply enmeshed in the global financial system. The results show that one of the most important reasons for the drop in the natural rate was weaker growth. In the 1960s and ’70s, a swelling workforce and rapid productivity gains meant average annual growth of gross domestic product was close to 4%. Strong growth created a powerful incentive to invest—lifting the price of money.

By the 2000s those drivers were running out of steam. After the global financial crisis of 2007-08, average annual GDP growth slumped to around 2%. A more sluggish economy meant the attractiveness of investing for the future was weaker—dragging the price of money lower.

Shifting demographics contributed in another way. From the 1980s on, as the baby boom generation started squirreling away more money for retirement, the supply of saving went up—adding more downward pressure on the natural rate.

Other factors also contributed. On the saving side of the equation, China’s economy was growing fast, saving a lot and channeling those savings into US government bonds. And in the US, income inequality went up—high earners tuck away a higher share of their income, which further increased the supply of saving.

On the investment side, computers got cheaper and more powerful, meaning companies didn’t have to spend so much upgrading their technology—lowering investment demand and dragging the natural rate lower.

For the US economy, that fall in the price of money had profound consequences. Bargain-basement borrowing costs meant households could take on bigger mortgages. In the early 2000s many bit off more than they could chew. There were lots of reasons behind the subprime mortgage meltdown and global financial crisis; falling borrowing costs were one.

And cheaper money meant that even as US federal debt almost tripled, from 33% of GDP at the turn of the century to nearly 100% today, the cost of servicing that debt remained low, allowing the government to continue spending on education, infrastructure and the military.

For the Federal Reserve, a lower natural rate meant less space to cut rates during recessions, leading to much hand-wringing about the diminished firepower of monetary policy.

(to be continued)

Translation

（彭博）－全球經濟中最重要的價格是什么？ 石油價格？ 半導體的價格？ 巨無霸的價格？ 比這些都更重要的是貨幣的價格。 三十多年來，它一直在下降。 現在它正在上漲。 如果問大多數人貨幣價格是如何設定的，他們會說央行。 誠然，當談到直接控制美國利率時，是由美國聯儲局會發號施令。 但還有更深層的邏輯在運作。 從根本上來說，貨幣的價格 - 就像其他任何東西的價格一樣 - 反映了供求平衡。 更多儲蓄會壓低利率。 更多的投資需求推高對貨幣供應要求。

對經濟學迷來說, 平衡儲蓄和投資同時維持通膨穩定的貨幣價格還有另一個名字：「自然利率」。 要了解為什麼這個概念對於政策制定至關重要，想想如果聯儲局將借貸成本設定為遠低於自然利率，會發生什麼事。 如果貨幣太便宜，投資就會過多，儲蓄就會不足，經濟就會過熱，導致通貨膨脹螺旋上升。 反過來說，如果聯儲局將借貸成本設定為高於自然利率，儲蓄就會過多，投資就會不足，經濟就會降溫，導致失業率上升。

三十多年來，美國的借貸成本呈現下降趨勢。 根據我們的估計，並加入通貨膨脹因數進行調整，10年期美國政府債券的自然利率從1980年的略高於5%下降到過去十年中的略低於2%。

為了找出推動利率下降的原因，並預測未來自然利率的走向，我們建立了一個模型，描述驅動儲蓄供給和投資需求的主要因素。 我們的資料收集跨越了半個世紀，涉及 12 個深深融入全球金融體系的已開發經濟體。 結果顯示，自然利率下降的最重要原因之一是成長疲軟。 在 1960 年代和 1970 年代，勞動力的膨脹和生產率的快速提高意味著國內生產總值的年均增長率接近 4%。 強勁的成長創造了強大的投資意欲 - 推高了貨幣價格。

到了 2000 年代，這些動力已經筋疲力盡。 2007-08年全球金融危機後，年均GDP成長率降至2%左右。 經濟更加低迷意味著未來投資的吸引力減弱，從而拖累貨幣價格走低。

人口結構的變化以另一種方式做出了貢獻。 從 1980 年代開始，隨著嬰兒潮世代開始為退休儲蓄更多的錢，儲蓄供給增加，自然利率面臨更大的下行壓力。

其他因素也有貢獻。 在儲蓄方面，中國經濟成長迅速，儲蓄大量，並將這些儲蓄轉化為美國政府債券。 在美國，收入不平等加劇 - 高收入者將更高比例的收入存起來，這進一步增加了儲蓄供應。

在投資方面，電腦變得更便宜、更強大，這意味著公司不必花費太多資金來升級技術，從而降低投資需求並拉低自然利率。

對美國經濟來說，貨幣價格的下跌產生了深遠的影響。 廉價的借貸成本意味著家庭可以承擔更大的抵押貸款。 2000 年代初，許多人貪得無厭。 次貸危機和全球金融危機背後的原因是多方面的； 借貸成本下降就是其中之一。

更便宜的資金意味著，儘管美國聯邦債務幾乎增加了兩倍，從世紀之交佔GDP 的33% 增加到今天的近100%，但償還債務的成本仍然很低，使政府能夠繼續在教育、基礎設施和軍隊的開支。

對聯儲局來說，較低的自然利率意味著經濟衰退期間降息的空間較小，導致因貨幣政策火力減弱而要絞盡腦汁。

（待續）

Cats have 276 different facial expressions, identified by American cat-loving researchers

Recently CNN.co.jp reported the following:

猫の表情は２７６種類、米の猫好き研究者が特定

2023.11.02 Thu posted at 13:37 JST

（ＣＮＮ） 耳を倒したり、目を見開いたり、口の周りをなめたり――。米国の研究チームが猫のそんな顔を調べて２７６種類の表情を特定した。

論文は猫好きな研究者２人が先月、学術誌に発表した。筆者の１人、米ライオンカレッジのブリタニー・フローキウィッツ氏は１日、ＣＮＮの取材に「猫のコミュニケーションはこれまで考えられていたよりずっと複雑だったことが、今回の研究で分かった」と話している。

共同研究者でカンザス医科大学の学生ローレン・スコット氏は、フローキウィッツ氏と共にカリフォルニア大学ロサンゼルス校に在籍していた２０２１年８月から２２年６月にかけ、地元の猫カフェで５３匹の猫を撮影。１９４分の映像から１８６回の猫の交流を記録した。猫は成体の短毛種で、全頭が避妊・去勢されていた。

記録した表情について、猫の顔の筋肉の動きを観察するシステムを使って調べた結果、形態学的に識別できる２７６種類を特定した。呼吸やあくびといった生体作用に関連する筋肉の動きは除外している。

それぞれの表情の意味は特定できなかったものの、４５．７％は和やかな表情、３７％は攻撃的な表情と分類している。

耳やヒゲが前を向いて目を閉じているのは和んでいる表情、目を見開いて耳を頭に付けるように倒し、口の周りをなめるのは攻撃的な表情と分類された。

イエネコは人間の近くにいることからノネコに比べて社会的寛容性が高く、猫同士の交流が増えるために表情が豊かになるとフローキウィッツ氏は解説する。

今後は猫の表情の意味について、さらに研究を深めたいとしている。

Translation

(CNN) The ears folded down, eyes widened, and licking around the mouth. A research team from the United States studied the faces of cats and identified 276 different facial expressions.

The paper was published in an academic journal last month by two cat-loving researchers. One of the authors, Brittany Frokiewicz from Lyon College in the US told CNN on the 1^st that ``This study shows that cat communication is much more complex than previously thought.''

Co-researcher Lauren Scott, a student at the University of Kansas Medical School, photographing 53 cats at a local cat cafe between August 2021 and June 2022, while she and Frokiewicz were both students at the University of California, Los Angeles. They recorded 186 cat interactions from 194 minutes of footage. All cats were adult short-haired cats and had been spayed or neutered.

As a result of examining the recorded facial expressions using a system that observed the movements of cat facial muscles, they identified 276 types that could be morphologically distinguished. Muscle movements related to biological actions such as breathing and yawning were excluded.

Although the meaning of each expression could not be determined, 45.7% were classified as peaceful expressions and 37% as aggressive expressions.

With its ears and whiskers pointing forward and its eyes closed was classified as a calm expression, while with its eyes opened, ears folded down to the head, and licking around the mouth was classified as an aggressive expression.

Frokewicz explained that domestic cats had higher social tolerance than feral cats because they lived close to humans, and their facial expressions became richer because of the increased interaction between cats.

In the future, he would like to further research into the meaning of cats' facial expressions.

              So, a research has studied the faces of cats and identified 276 different facial expressions. One researcher explains that domestic cats have higher social tolerance than feral cats because they live close to humans, and their facial expressions become richer because of the increased interaction between cats. I am wondering to want extent do cats understand each other’s facial expressing.