3. Business – Page 23

LDI debt deadlock heads for legal review

ISLAMABAD:

A sub-committee of the NA Standing Committee on Information Technology met on Thursday to review the ongoing issue of outstanding dues owed by Long Distance and International (LDI) companies to the PTA.

The panel decided to seek legal opinion from the Ministry of Law regarding the recovery issue.

During the meeting, the PTA chairman stated that the authority is not empowered to allow installment-based payments for the recovery of dues from LDI operators. “PTA does not have the authority to restructure or defer the payment of dues in installments,” he said.

The PTA chairman added that several rounds of meetings have been held with defaulting LDI companies, but their stance on dues repayment continues to differ.

“After hearing their views, we have issued letters to the companies, and a clear decision has been communicated; outstanding dues must be paid in full, including late payment charges,” he noted.

The LDI representatives stated that they had offered the PTA to pay the principal amount in installments and expressed readiness to issue post-dated cheques.

The PTA insisted that all dues, including late fees, must be deposited into an escrow account.

The LDI representatives maintained that there was a lack of clarity in government policy regarding the renewal of their licenses.

The IT secretary observed that the issue of dues with the LDI companies was not “straightforward”, noting that each company had a different position. “Whatever decision the government takes will set a precedent for dues recovery in other sectors as well,” he noted.

The PTA chairman revealed that not all LDI companies have agreed to pay the principal amount.

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July 31, 2025

Apple announces Q3 results with 10 pct revenue increase-Xinhua

SAN FRANCISCO, July 31 (Xinhua) — Apple on Thursday announced financial results for its fiscal 2025 third quarter that ended on June 28, with quarterly revenue of 94 billion U.S. dollars, up 10 percent year over year.

The company posted quarterly diluted earnings per share of 1.57 dollars, up 12 percent year over year. Its net income for the quarter increased to 23.43 billion dollars from 21.45 billion dollars a year ago.

Sales of iPhones rose to 44.58 billion dollars from 39.3 billion dollars a year ago. Its Mac sales increased to 8.05 billion dollars from 7.01 billion dollars a year ago.

The company’s services income was 27.42 billion dollars, up from 24.21 billion dollars the previous year.

The sales of wearables, home and accessories products decreased to 7.4 billion dollars from 8.1 billion dollars a year ago.

“Today Apple is proud to report a June quarter revenue record with double-digit growth in iPhone, Mac and Services and growth around the world, in every geographic segment,” said Tim Cook, Apple’s CEO.

“We are very pleased with our record business performance for the June quarter, which generated EPS (earnings per share) growth of 12 percent,” said Kevan Parekh, Apple’s CFO.

Apple’s board of directors has declared a cash dividend of 0.26 dollars per share of the company’s common stock. ■

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July 31, 2025

Lundin Mining Announces Updated Share Capital and Provides Update on Share Buybacks

July 31, 2025

VANCOUVER, BC, July 31, 2025 /CNW/ – (TSX: LUN) (Nasdaq Stockholm: LUMI) Lundin Mining Corporation (“Lundin Mining” or the “Company”) reports the following updated share capital and voting rights, in accordance with the Swedish Financial Instruments Trading Act.

The number of issued and outstanding shares of the Company has increased by 3,331 to 856,000,994 common shares with voting rights as of July 31, 2025. The increase in the number of issued and outstanding shares from June 30, 2025 to date is a result of the exercise of employee stock options or the vesting of employee share units. During this period, the Company did not purchase any shares for cancelation under its Normal Course Issuer Bid program.

Normal Course Issuer Bid

Under the Company’s shareholder distribution policy, the Company is committed to allocating up to US$150 million in annual share buybacks through the NCIB program. So far during 2025, Lundin Mining has acquired 12,629,000 common shares at a cost of approximately US$104 million.

About Lundin Mining

Lundin Mining is a diversified base metals mining company with operations or projects in Argentina, Brazil, Chile, and the United States of America, primarily producing copper, gold and nickel.

The information in this release is subject to the disclosure requirements of Lundin Mining under the Swedish Financial Instruments Trading Act. The information was submitted for publication, through the agency of the contact persons set out below on July 31, 2025 at 16:00 Pacific Time.

Lundin Mining Announces Updated Share Capital and Provides Update on Share Buybacks (CNW Group/Lundin Mining Corporation)

SOURCE Lundin Mining Corporation

For further information, please contact: Stephen Williams, Vice President, Investor Relations: +1 604 806 3074; Robert Eriksson, Investor Relations Sweden: +46 8 440 54 50

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July 31, 2025

How global CEOs are shifting gears

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July 31, 2025

Filtering labour market data optimally to detect recessions early and accurately

The timely detection of recessions is critical for an effective policy response. Yet, in the US, the official declaration from the NBER Business Cycle Dating Committee arrives many months, sometimes more than a year, after a recession has begun. For policymakers who need to make decisions in real time, this delay is impractical.

To address this lag, researchers have for many decades developed algorithms to detect recession starts as early as possible (see Hamilton 2011 for a survey of the literature). Among existing algorithms, threshold rules that use the unemployment rate, such as the Sahm (2019) rule, have been found to perform well at detecting recessions early (Crump et al. 2020).

However, such rules are based on a single noisy measure of the economy. By combining unemployment data with vacancy data, it is possible to obtain a less noisy signal, and thus to detect recessions more quickly and robustly (Michaillat and Saez 2025). The basis for this insight is the Beveridge curve: at the onset of every recession, unemployment rises sharply just as job vacancies drop (Figure 1).

Figure 1 Monthly US unemployment and vacancy rates, April 1929–May 2025

Sources: Barnichon (2010), Petrosky-Nadeau and Zhang (2021), and Bureau of Labour Statistics.

In a new paper, I take the next logical step: instead of using one specific formula to filter and combine labour market data, the algorithm systematically searches for the optimal way to do so (Michaillat 2025). The goal is to find the best possible lens to view the data, to extract as much real-time information as possible from them.

The recession detection algorithm that I develop first generates millions of recession classifiers, each processing the unemployment and vacancy data in a unique way, and each using a unique recession threshold. The algorithm then only keeps the classifiers that make no errors over the 1929–2021 training period. To be selected, a classifier must therefore identify all 15 US recessions between 1929 and 2021 without a single false positive. This leaves us with over two million historically perfect classifiers.

Having millions of perfect classifiers creates a new challenge: which one to choose? To solve this, the algorithm evaluates classifiers on two key dimensions: how much they anticipate recession starts and how precise that signal is. By plotting each classifier’s average detection error against the standard deviation of the detection error, the algorithm identifies an anticipation-precision frontier – classifiers that offer the best combinations of foresight and accuracy (Figure 2). From this frontier, the algorithm then picks all the classifiers whose detection error’s standard deviation is below 3 months – which guarantees that the width of the 95% confidence interval for the estimated recession start date is less than 1 year. Overall, the algorithm selects an ensemble of 7 recession classifiers.

Figure 2 Two million perfect recession classifiers for the US, April 1929–December 2021, and the anticipation-precision frontier

Notes: The figure displays the mean and standard deviation of the detection errors for 2,343,752 perfect classifiers, which detect the 15 recessions that occurred between 1929 and 2021 without false positives.

So, is the US economy in a recession now? The classifier ensemble provides a single, real-time recession probability. When I apply the ensemble to the most recent data, it says that the recession probability has reached 71% in May 2025 (Figure 3). Since mid-2022, the combination of rising unemployment and falling vacancies has triggered 5 of the 7 classifiers in the ensemble, pushing the recession probability up. The recession probability first became positive late in 2023, when 3 of the 7 classifiers got triggered. The recession further increased in the middle of 2024, when 2 additional classifiers got activated. Currently, only 2 of the 7 classifiers in the ensemble remain inactivated.

Figure 3 Recession probability from the classifier ensemble trained on US data, April 1929–December 2021

Notes: The probability is the average of the probabilities given by the individual classifiers in the ensemble (thin orange lines). The classifiers in the ensemble are selected from the high-precision segment of the 1929–2021 anticipation-precision frontier.

Given the recent records on the US stock market, isn’t it strange that the algorithm produces such a high recession probability? What explains it in the underlying labour market data? This substantial recession probability is due to the noticeable decrease in the number of job vacancies and increase in the number of job seekers since the middle of 2022 (Figure 1). The vacancy rate fell by 43%, from 7.40% in April 2022 down to 4.21% in April 2025. The unemployment rate increased by 23%, from 3.46% in January 2023 up to 4.24% in May 2025. (These data can be visualised here). Such adverse changes in labour market conditions are typically associated with a recession, which is why 5 of the 7 classifiers switched on since the middle of 2023.

What is odd about the current period is that the recession risk has remained elevated without increasing further for about a year. By contrast, during the 15 recessions of the training period, once the recession probability turned positive, it rapidly rose to 1. The reason for this strange behaviour is that, after cooling significantly between the middle of 2022 and the middle of 2024, the US labour market stopped cooling and remained at a standstill between the middle of 2024 and today. Such a pause in cooling is very unusual.

To verify the model’s reliability, I performed several backtests. For instance, I trained the algorithm using data only up to December 1984 and asked it to detect all subsequent recessions. All the classifiers in the ensemble built from 1929–1984 data did very well, correctly identifying all four recessions in the 1985–2021 test period – including the dot-com bust and the Great Recession – without any false positives. Even without seeing any data past 1984, the classifier ensemble detected the Great Recession in good time, with its recession probability surging by the summer of 2008, providing a clear and timely warning. In fact, the performance of the algorithm over the entire testing period, 1985–2021, is surprisingly good: the standard deviation of errors averages only 1.4 months, and the mean error averages only 1.2 months.

What is the current recession risk according to the classifier ensemble trained on 1929–1984 data? That classifier ensemble assigns a recession probability of 83% to current data (Figure 4). This is because 5 of the 6 classifiers in the ensemble are currently triggered. In fact, according to that ensemble, the recession probability reached 100% in the middle of 2024, before dropping slightly in early 2025. The classifier ensembles produced in other backtests also produce elevated recession probabilities in May 2025.

Figure 4 Recession probability from the classifier ensemble trained on US data, April 1929–December 1984

Notes: The probability is the average of the probabilities given by the individual classifiers in the ensemble (thin orange lines). The classifiers in the ensemble are selected from the high-precision segment of the 1929–1984 anticipation-precision frontier.

Next, to ensure that the algorithm is not overfitting the data, I run a placebo test. I ask the algorithm to detect a series of events that are random, as frequent as recessions but not connected in any way to the US economy. The events that I pick are the deaths of 15 US first ladies between 1929 and 2021: Helen Taft, Lou Hoover, Frances Cleveland, Edith Roosevelt, Grace Coolidge, Edith Wilson, Eleanor Roosevelt, Mamie Eisenhower, Bess Truman, Pat Nixon, Jacqueline Kennedy, Lady Bird Johnson, Betty Ford, Nancy Reagan, and Barbara Bush.

The algorithm is unable to detect these placebo events (Figure 5). The standard deviation of the algorithm’s detection errors for the first-lady deaths exceeds 40 years – while this standard deviation was less than 2 months for recessions. This stark failure in the first-lady placebo test demonstrates that the model identifies genuine economic signals rather than spuriously fitting the data.

Figure 5 Placebo test of the algorithm: Detecting the deaths of US first ladies with labour market data

Finally, I examine whether it is possible to detect recessions earlier and more accurately by applying the algorithm to some of the product market data used by the NBER Dating Committee. Unlike the algorithm presented in this paper, the NBER relies mostly on product market metrics (production, sales, consumption) to date recessions. The committee states that it does not look at the unemployment rate because it is ‘lagging’ and ‘noisy’. So I apply the algorithm to data on industrial production – which are also available since 1929.

I find that the combination of unemployment and vacancy rates consistently outperforms industrial production in providing early and accurate recession signals; in fact the unemployment rate alone outperforms industrial production (Figure 6). Even when combined, unemployment and industrial production data do not achieve the same level of anticipation and precision as the unemployment-vacancy pairing, suggesting that current official dating practices might benefit from a greater emphasis on unemployment and vacancies.

Figure 6 Comparing labour market classifiers to product market classifiers

Overall, this new algorithm shows that the US labour market is sending an unambiguous signal: the conditions characteristic of a recession are not on the horizon – they are already here. If it turns out, once the dust has settled, that the US economy is not in a recession, what would we learn? In that case, the algorithm could be retrained on the new data. The 5 classifiers that mistakenly detected the recession would be eliminated, while the 2 classifiers that did not detect a recession would be retained. Given that several of the classifiers on the frontier do signal a recession, the anticipation-precision frontier would shift out. We would therefore learn that detecting recessions with labour market data is harder than previous recessions suggested, because the current period is not following previous patterns.

References

Barnichon, R (2010), “Building a composite help-wanted index”, Economics Letters 109(3): 175–78.

Crump, R, D Giannone, and D Lucca (2020), “Reading the tea leaves of the US business cycle”, Liberty Street Economics, Federal Reserve Bank of New York.

Hamilton, J D (2011), “Calling recessions in real time”, International Journal of Forecasting 27(4): 1006–1026.

Michaillat, P (2025), “Early and accurate recession detection using classifiers on the anticipation-precision frontier”, arXiv:2506.09664v3.

Michaillat, P, and E Saez (2025), “Has the recession started?”, Oxford Bulletin of Economics and Statistics.

Petrosky-Nadeau, N, and L Zhang (2021), “Unemployment crises”, Journal of Monetary Economics 117: 335–53.

Sahm, C (2019), “Direct stimulus payments to individuals”, in H Boushey, R Nunn, and J Shambaugh (eds.), Recession Ready: Fiscal Policies to Stabilize the American Economy, Washington, DC: Brookings Institution.

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July 31, 2025

The ripple beyond borders: Indirect effects of US export controls on Japanese firms

Since the initiation of the US-China trade war in the latter half of the 2010s, the US government has strengthened export control regulations. Specifically, many Chinese firms have been added to the Entity List (EL), a list of parties of concern. These regulations have decoupled US firms from Chinese firms in supply chains. For example, Crosignani et al. (2024) found that US firms that had supplied Chinese firms included on the Entity List were more likely to terminate their relationships with Chinese customers – both those listed and not listed. Furthermore, Chinese firms in the Entity List reduced their relationships with US suppliers and established new connections with alternative Chinese suppliers.

In May 2019, the US added Huawei Technologies Co., Ltd. (hereafter, Huawei) and its 68 affiliates to the Entity List. Huawei is a Chinese company that designs, develops, manufactures, and sells telecommunications equipment, consumer electronics, and smart devices, such as smartphones. Furthermore, since 2020, the US government has expanded the Foreign Direct Product Rule (FDPR) to restrict the exports of cutting-edge semiconductors from third countries to Huawei and its affiliates on the Entity List. These extended FDPRs have stopped exports of cutting-edge semiconductors to Huawei. The major manufacturers of such products, such as Korean and Taiwanese firms, have stopped supplying cutting-edge chips to Huawei since September 2020.

Japanese firms, on the other hand, are not major producers of cutting-edge semiconductors and thus are not subject to the above-mentioned direct effects of the regulations. However, before the introduction of the extended FDPR, Japanese firms were the top suppliers to Huawei in terms of the number of parts for Huawei smartphones (Huawei P30 Pro). In terms of input value, Japanese firms were the second-largest group of suppliers following Chinese firms. Therefore, Japanese suppliers would suffer adverse impacts on their exports to Huawei if Huawei were to stop production due to the termination of imports of cutting-edge semiconductors.

Although many studies have examined the trade effects of tariff wars, few have explored export control regulations in the context of the US-China trade war. Among these few, some studies analyse the impact of tightened US export restrictions on Chinese firms’ innovation, including the aforementioned study of Crosignani et al. (2024), which examines the effects on transactions between US and Chinese firms. Furthermore, there has been little analysis of the impact of the tightening of US export restrictions on third-country firms, such as those in Japan, in terms of their exports and sales.

Against this backdrop, in Hayakawa and Ito (2025) we empirically examined the indirect effect of US export regulations on exports by Japanese suppliers to Huawei. Unlike Crosignani et al. (2024), we focus on the impact on suppliers in a third country (i.e. Japan). Moreover, although there are some product-level studies investigating the effects of US export regulations on export from Japan to China (Hayakawa et al. 2023, Ando et al. 2024, Hayakawa et al. 2025) or from South Korea to China (Kim and Cho 2024) based on customs statistics, in Hayakawa and Ito (2025) we utilise firm-level data. This allows us to investigate the heterogeneous effects across firms as well as the average effects, controlling for various firm characteristics.

As mentioned above, Japanese suppliers do not export cutting-edge semiconductors that are subject to the Foreign Direct Product Rule. Therefore, if they are affected by the US export restrictions on China, it would be an indirect impact, which might be termed collateral damage. To investigate such collateral damage, we identified 17 Japanese firms that were major suppliers to Huawei and applied the difference-in-differences method using Japanese firm-level data from 2016 to 2021. We focus on firms in telecommunications equipment and electronic components that had directly exported to China between 2016 and 2018. Among these, the above-identified 17 firms and their affiliates were designated as the treatment group, and the other firms were designated as the control group.

One empirical challenge is that Huawei’s suppliers should have different characteristics from those of other firms. As Huawei is a large company, it only selects large and highly productive firms as suppliers. Indeed, among the firms analysed in Hayakawa and Ito (2025), treatment group firms tend to be larger than control group firms, as expected. Therefore, we match each treatment group firm with a firm in the same sector that shares a similar size and other characteristics as the treated firm in 2018. Specifically, propensity scores are estimated using the covariate-balancing propensity score estimator. Then, using weights based on those scores, we estimate the average treatment effect on the treatment group firms via a weighted least squares regression.

The results confirmed that the US government’s addition of Huawei to the Entity List, along with the strengthening of the Foreign Direct Product Rule, reduced the exports of Japanese Huawei suppliers to China in 2020 (Figure 1), particularly their exports to unaffiliated firms in China. Suppliers that were heavily engaged in research and development (R&D) activities further reduced their exports, especially in terms of inter-firm exports to China, in 2021. One possible interpretation of this result is that suppliers of low-tech inputs can more easily find alternative customers, that is, customers other than Huawei, because their inputs are less customised. Thus, inter-firm exports to China recovered by 2021. By contrast, since high-tech input suppliers need more time to customise their inputs for other customers, they still exhibited a decrease in their inter-firm exports to China in 2021. These results imply that the negative effects of export control regulations are greater for suppliers that either produce or provide high-tech or customised inputs.

Figure 1 Effects of the US regulations on Japanese firms’ exports to China: Before and after the addition of Huawei to the Entity List

Notes: The figure shows the estimated differences in the log of exports to China between Huawei suppliers (treated firms) and other firms (control firms) before and after Huawei was added to the Entity List. The blue bar represents the 95% confidence interval. The estimates are based on a weighted OLS regression, using the weights calculated from the estimated propensity score for each firm.
Source: Hayakawa and Ito (2025) Figure 3 (a).

On the other hand, while Japanese suppliers to Huawei did not clearly increase their total exports to countries other than China after Huawei was added to the Entity List, they significantly increased exports to their overseas affiliates located in countries or regions outside China by 2021 (Figure 2). This suggests a growing preference among Japanese Huawei suppliers for less risky alternatives. Furthermore, the study found that total sales of Japanese Huawei suppliers remained stable or even increased. Thus, it appears that, so far, US sanctions on Huawei have not had a significant effect on the overall performance of Japanese suppliers to Huawei.

Figure 2 Effects of the US regulations on Japanese firms’ intra-firm exports to other regions

Notes: The figures show the estimated differences in the log of exports to all regions except China between Huawei suppliers (treated firms) and other firms (control firms) before and after Huawei was added to the Entity List. The blue bar represents the 95% confidence interval. The estimates are based on a weighted OLS regression, using the weights calculated from the estimated propensity score for each firm.
Source: Hayakawa and Ito (2025) Figure 5 (a).

To summarise, this column focuses on the impact of export restrictions in the US-China trade war on the supply chain, particularly on suppliers in third countries (Japan), and provides important insights into understanding the complex ripple effects of export restrictions. Export restrictions on Huawei temporarily reduced Japanese suppliers’ exports to China, but the impact was limited. However, in response to the tightening of restrictions, Japanese suppliers tended to shift to less risky export destinations, suggesting that the restrictions prompted changes in their export behaviour.

If trade restrictions continue to spread between the US and China, or to other countries, firms need to develop new export destinations, which will incur higher costs associated with such diversification. Furthermore, if changes in the export behaviour of individual firms damage the efficiency of the supply chain as a whole, it could lead to stagnation in global trade. Governments in each country need to provide clearer information on regulations and strengthen their support for the development of new export destinations and business partners.

The Supply Chain Agreement, which came into effect in 2024 under the Indo-Pacific Economic Framework (IPEF) launched in May 2022 under the Biden administration, stipulates “cooperation to strengthen supply chains and promote transparency in the actions and regulations of each country.” However, with the second Trump administration taking office in 2025, it is unclear whether the IPEF-related initiatives by each country will progress. While multilateral cooperation involving the US is desirable, it is crucial to advance cooperation among governments by leveraging existing frameworks such as bilateral and regional trade agreements.

Authors’ note: The main research on which this column is based (Hayakawa and Ito 2025) first appeared as a Discussion Paper of the Research Institute of Economy, Trade and Industry (RIETI) of Japan.

References

Ando, M, K Hayakawa and F Kimura (2024), “Supply Chain Decoupling: Geopolitical Debates and Economic Dynamism in East Asia”, Asian Economic Policy Review 19(1): 62-79.

Crosignani, M, L Han, M Macchiavelli and A F Silva (2024), “Geopolitical Risk and Decoupling: Evidence from U.S. Export Controls”, Staff Reports 1096, Federal Reserve Bank of New York.

Hayakawa, K and K Ito (2025), “The Collateral Damage of US Export Control Regulations on Japanese Suppliers’ Exports to China”, Discussion papers 25061, Research Institute of Economy, Trade and Industry (RIETI).

Hayakawa, K, K Ito, K Fukao and I Deseatnicov (2023), “The Impact of the Strengthening of Export Controls on Japanese Exports of Dual-Use Goods”, International Economics 174: 160-179.

Hayakawa, K, F Kimura and K Yamanouchi (2025), “The Trade Effects of Export Control Regulations in Japan”, Journal of the Japanese and International Economies 77: 101366.

Kim, H and J Cho (2024), “The Impact of US Export Controls on Korean Semiconductor Exports”, KDI Journal of Economic Policy 46(3): 1–23.

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July 31, 2025

State Council executive meeting calls for good economic work in H2

BEIJING, July 31 — A State Council executive meeting on Thursday called for consolidating and boosting the momentum of economic recovery in the second half of the year.

The meeting, presided over by Chinese Premier Li Qiang, studied and implemented the guiding principles of an important speech by Xi Jinping, general secretary of the Communist Party of China (CPC) Central Committee, on the current economic situation and arrangements for economic work in the second half of 2025.

The meeting emphasized the need to develop a good understanding of the CPC Central Committee’s scientific judgment of the economic situation, and to further enhance the sense of mission and responsibility in doing good economic work in the second half.

Targeting annual development goals and tasks, more efforts should be made to boost the effectiveness of macro policies, stimulate the endogenous power of economic development, and better coordinate development and security, the meeting said.

It also reviewed and approved a document on boosting the large-scale commercial application of artificial intelligence, arranged the implementation of interest subsidy policies for personal consumption loans and lending for service sector business entities, and discussed and approved in principle a draft law on the protection and quality improvement of arable land.

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July 31, 2025

IMF Executive Board Completes First Review of the Extended Arrangement Under the Extended Fund Facility for Argentina – International Monetary Fund

IMF Executive Board Completes First Review of the Extended Arrangement Under the Extended Fund Facility for Argentina International Monetary Fund
Argentina Starts Building Up ‘Critically Low’ Cash Reserves: Shock Therapy Bloomberg
IMF board approves $2 billion for Argentina TradingView
IMF Board Completes First Argentina Program Review, Approves $2 Billion Disbursement Money/ US News

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July 31, 2025

Figma’s 250% IPO Pop Gives It Edge in Creative AI Software Fight

(Bloomberg) — Figma Inc.’s 250% surge in its debut session is the kind of coming-out party every startup dreams of when it goes public.

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July 31, 2025

AES Reports Second Quarter 2025 Results; On Track to Deliver on 2025 Guidance and Long-Term Targets

Second Quarter 2025 Renewables SBU Adjusted EBITDA Grew 56% Versus Second Quarter 2024

Strategic Accomplishments

On track to add 3.2 GW of new projects in operation in 2025
- 1.9 GW already completed
- Remaining 1.3 GW 78% complete
Since the first quarter call in May, signed or awarded new long-term PPAs for 1.6 GW of solar and wind, all with data center companies
PPA backlog of 12 GW, including 5.2 GW under construction
AES Indiana filed a petition for regulatory rate review with the Indiana Utility Regulatory Commission (IURC)

Q2 2025 Financial Highlights

GAAP Financial Metrics
- Net Loss of $150 million, compared to Net Income of $153 million in Q2 2024
- Net Loss Attributable to The AES Corporation of $95 million, compared to Net Income Attributable to The AES Corporation of $276 million in Q2 2024
- Diluted EPS of ($0.15), compared to $0.39 in Q2 2024
Non-GAAP Adjusted Financial Metrics
- Adjusted EBITDA¹ of $681 million, compared to $658 million in Q2 2024
- Adjusted EBITDA with Tax Attributes¹^,2 of $1,057 million, compared to $849 million in Q2 2024
- Adjusted EPS³ of $0.51, compared to $0.38 in Q2 2024

Financial Position and Outlook

Reaffirming 2025 guidance for Adjusted EBITDA¹ of $2,650 to $2,850 million
- Reaffirming annualized growth target of 5% to 7% through 2027, off a base of 2023 guidance
- Reaffirming expectation for 2025 Adjusted EBITDA with Tax Attributes^1,2 of $3,950 to $4,350 million
Reaffirming 2025 guidance for Adjusted EPS³ of $2.10 to $2.26
- Reaffirming annualized growth target of 7% to 9% through 2025, off a base of 2020 and 7% to 9% through 2027, off a base of 2023 guidance

ARLINGTON, Va., July 31, 2025 /PRNewswire/ — The AES Corporation (NYSE: AES) today reported financial results for the quarter ended June 30, 2025.

“AES is in a uniquely strong position due to our diversified operating portfolio, well-protected 12 GW backlog of signed long-term PPAs, and established domestic supply chain,” said Andrés Gluski, AES President and Chief Executive Officer. “With 1.6 GW of signed PPAs with data centers since our first quarter results in May, we are a leader in the fastest growing segment in the market.”

“We made excellent progress during the second quarter of 2025, as demonstrated by the robust growth in Adjusted EBITDA at our Renewables SBU, which was 56% higher than in the same period last year,” said Stephen Coughlin, AES Executive Vice President and Chief Financial Officer. “Our strong track record with our customers, resilient supply chain strategy, and advanced construction execution enable us to confidently reaffirm both our 2025 guidance and long-term growth rate targets through 2027.”

Q2 2025 Financial Results

Second quarter 2025 Net Loss was $150 million, a decrease of $303 million compared to Net Income of $153 million in second quarter 2024, primarily due to higher day-one losses on sales type leases at AES Clean Energy Development⁴. In addition, Net Income was negatively impacted by higher income tax expense, lower margins from the Energy Infrastructure Strategic Business Unit (SBU) from prior year unrealized derivative gains and higher prior year revenues from the monetization of the Warrior Run coal plant PPA. This decrease was partially offset by the impact of reclassifying Mong Duong from held-for-sale to held and used, and higher contributions from renewables projects placed in service in the current year.

Second quarter 2025 Adjusted EBITDA⁵ (a non-GAAP financial measure) was $681 million, an increase of $23 million compared to second quarter 2024, driven by higher contributions from the Renewables SBU primarily due to higher revenues from renewables projects placed in service and prior year outages in Colombia. This was partially offset by the sale of AES Brasil, higher prior year revenues from the monetization of the Warrior Run coal plant PPA, and the impact of the sell-down of AES Ohio in the Utilities SBU.

Second quarter 2025 Adjusted EBITDA with Tax Attributes^5,6 (a non-GAAP financial measure) was $1,057 million, an increase of $208 million compared to second quarter 2024, due to higher realized tax attributes driven by more projects placed in service and higher income from tax credit transfers, as well as the drivers above.

Second quarter 2025 Diluted Earnings Per Share from Continuing Operations (Diluted EPS) was ($0.15), a decrease of $0.54 compared to second quarter 2024, mainly driven by higher income tax expense, day-one losses on the commencement of sales-type leases at AES Clean Energy Development, and lower earnings at the Energy Infrastructure SBU primarily due to higher prior year revenues from the monetization of the Warrior Run coal plant PPA. This was partially offset by the derecognition of a valuation allowance on the loan receivable upon reclassifying Mong Duong from held-for-sale to held and used.

Second quarter 2025 Adjusted Earnings Per Share⁷ (Adjusted EPS, a non-GAAP financial measure) was $0.51, an increase of $0.13 compared to second quarter 2024, mainly driven by a lower adjusted tax rate and higher contributions due to new renewables projects placed in service, partially offset by lower contributions from the Utilities SBU due to planned outages.

Strategic Accomplishments

The Company’s backlog, which consists of projects with signed contracts, but which are not yet operational, is 12 GW, including 5.2 GW under construction. Since the Company’s first quarter 2025 earnings call in May 2025, the Company:
- Completed the construction of 1.2 GW of energy storage and solar, including the 1 GW Bellefield 1 solar-plus-storage facility, for a total of 1.9 GW year-to-date, and is on track to add a total of 3.2 GW to its operating portfolio by year-end 2025; and
- Signed or was awarded new long-term PPAs for 1.6 GW of renewables, all with data center companies, and a total of 2 GW year-to-date.
In June, AES Indiana filed a petition for regulatory rate review with the Indiana Utility Regulatory Commission (IURC).
- This is AES Indiana’s first rate case using a forward-looking test year, which will enable a more efficient investment program to best serve customers with cost-effective and reliable electricity service.

Guidance and Expectations^8,10

The Company is reaffirming its 2025 guidance for Adjusted EBITDA⁸ of $2,650 to $2,850 million. Growth in 2025 is expected to be driven by contributions from new renewables projects, rate base growth at the Company’s US utilities, and normalized results in Colombia and Mexico, partially offset by revenues from the monetization of the Warrior Run coal plant PPA in 2024 and asset sales.

The Company is reaffirming its expectation for annualized growth in Adjusted EBITDA⁸ of 5% to 7% through 2027, from a base of its 2023 guidance of $2,600 to $2,900 million.

The Company is reaffirming its expectation that 2025 Adjusted EBITDA with Tax Attributes^8,9 of $3,950 to $4,350 million.

The Company is reaffirming its 2025 Adjusted EPS¹⁰ guidance of $2.10 to $2.26. Growth in 2025 is expected to be primarily driven by contributions from new renewables projects, rate base growth at the Company’s US utilities, and normalized results in Colombia and Mexico, partially offset by revenues from the monetization of the Warrior Run coal plant PPA in 2024, asset sales, higher Parent interest, and a higher adjusted tax rate.

The Company is reaffirming its annualized growth target for Adjusted EPS¹⁰ of 7% to 9% through 2025, from a base year of 2020. The Company is also reaffirming its annualized growth target for Adjusted EPS⁸ of 7% to 9% through 2027, from a base of its 2023 guidance of $1.65 to $1.75.

The Company’s 2025 guidance is based on foreign currency and commodity forward curves as of June 30, 2025.

The Company expects to maintain its current quarterly dividend payment of $0.17595 going forward.

Non-GAAP Financial Measures

See Non-GAAP Measures for definitions of Adjusted EBITDA, Adjusted EBITDA with Tax Attributes, Tax Attributes, Adjusted Earnings Per Share, and Adjusted Pre-Tax Contribution, as well as reconciliations to the most comparable GAAP financial measures.

Attachments

Condensed Consolidated Statements of Operations, Segment Information, Condensed Consolidated Balance Sheets, Condensed Consolidated Statements of Cash Flows, Non-GAAP Financial Measures and Parent Financial Information.

Conference Call Information

AES will host a conference call on Friday, August 1, 2025 at 10:00 a.m. Eastern Time (ET). Interested parties may listen to the teleconference by dialing 1-833-470-1428 at least ten minutes before the start of the call. International callers should dial +1-404-975-4839. The Participant Access Code for this call is 439668. Internet access to the conference call and presentation materials will be available on the AES website at www.aes.com by selecting “Investors” and then “Presentations and Webcasts.”

A webcast replay will be accessible at www.aes.com beginning shortly after the completion of the call.


¹	Adjusted EBITDA is a non-GAAP financial measure. See attached “Non-GAAP Measures” for definition of Adjusted EBITDA and a description of the adjustments to reconcile Adjusted EBITDA to Net Income (Loss) for the quarter ended June 30, 2025. The Company is not able to provide a corresponding GAAP equivalent or reconciliation for its Adjusted EBITDA guidance without unreasonable effort.
²	Pre-tax effect of Production Tax Credits, Investment Tax Credits, and depreciation tax deductions allocated to tax equity investors, as well as the tax benefit recorded from tax credits retained or transferred to third parties.
³	Adjusted EPS is a non-GAAP financial measure. See attached “Non-GAAP Measures” for definition of Adjusted EPS and a description of the adjustments to reconcile Adjusted EPS to Diluted EPS for the quarter ended June 30, 2025. The Company is not able to provide a corresponding GAAP equivalent or reconciliation for its Adjusted EPS guidance without unreasonable effort.
⁴	Losses recognized on the commencement of sales-type leases primarily relate to the exclusion of the value of Investment Tax Credits from the fair value of the renewable asset.
⁵	Adjusted EBITDA is a non-GAAP financial measure. See attached “Non-GAAP Measures” for definition of Adjusted EBITDA and a description of the adjustments to reconcile Adjusted EBITDA to Net Income for the quarter ended June 30, 2025. The Company is not able to provide a corresponding GAAP equivalent or reconciliation for its Adjusted EBITDA guidance without unreasonable effort.
⁶	Pre-tax effect of Production Tax Credits, Investment Tax Credits, and depreciation tax deductions allocated to tax equity investors, as well as the tax benefit recorded from tax credits retained or transferred to third parties.
⁷	Adjusted EPS is a non-GAAP financial measure. See attached “Non-GAAP Measures” for definition of Adjusted EPS and a description of the adjustments to reconcile Adjusted EPS to Diluted EPS for the quarter ended June 30, 2025. The Company is not able to provide a corresponding GAAP equivalent or reconciliation for its Adjusted EPS guidance without unreasonable effort.
⁸	Adjusted EBITDA is a non-GAAP financial measure. See attached “Non-GAAP Measures” for definition of Adjusted EBITDA and a description of the adjustments to reconcile Adjusted EBITDA to Net Income for the quarter ended June 30, 2025. The Company is not able to provide a corresponding GAAP equivalent or reconciliation for its Adjusted EBITDA guidance without unreasonable effort.
⁹	Pre-tax effect of Production Tax Credits, Investment Tax Credits, and depreciation tax deductions allocated to tax equity investors, as well as the tax benefit recorded from tax credits retained or transferred to third parties.
¹⁰	Adjusted EPS is a non-GAAP financial measure. See attached “Non-GAAP Measures” for definition of Adjusted EPS and a description of the adjustments to reconcile Adjusted EPS to Diluted EPS for the quarter ended June 30, 2025. The Company is not able to provide a corresponding GAAP equivalent or reconciliation for its Adjusted EPS guidance without unreasonable effort.

About AES

The AES Corporation (NYSE: AES) is a Fortune 500 global energy company accelerating the future of energy. Together with our many stakeholders, we’re improving lives by delivering the greener, smarter energy solutions the world needs. Our diverse workforce is committed to continuous innovation and operational excellence, while partnering with our customers on their strategic energy transitions and continuing to meet their energy needs today. For more information, visit www.aes.com.

Safe Harbor Disclosure

This news release contains forward-looking statements within the meaning of the Securities Act of 1933 and of the Securities Exchange Act of 1934. Such forward-looking statements include, but are not limited to, those related to future earnings, growth and financial and operating performance. Forward-looking statements are not intended to be a guarantee of future results, but instead constitute AES’ current expectations based on reasonable assumptions. Forecasted financial information is based on certain material assumptions. These assumptions include, but are not limited to, our expectations regarding accurate projections of future interest rates, commodity price and foreign currency pricing, continued normal levels of operating performance and electricity volume at our distribution companies and operational performance at our generation businesses consistent with historical levels, as well as the execution of PPAs, conversion of our backlog and growth investments at normalized investment levels, and rates of return consistent with prior experience.

Actual results could differ materially from those projected in our forward-looking statements due to risks, uncertainties and other factors. Important factors that could affect actual results are discussed in AES’ filings with the Securities and Exchange Commission (the “SEC”), including, but not limited to, the risks discussed under Item 1A: “Risk Factors” and Item 7: “Management’s Discussion & Analysis” in AES’ 2024 Annual Report on Form 10-K and in subsequent reports filed with the SEC. Readers are encouraged to read AES’ filings to learn more about the risk factors associated with AES’ business. AES undertakes no obligation to update or revise any forward-looking statements, whether as a result of new information, future events or otherwise, except where required by law.

Any Stockholder who desires a copy of the Company’s 2024 Annual Report on Form 10-K filed March 11, 2025 with the SEC may obtain a copy (excluding the exhibits thereto) without charge by addressing a request to the Office of the Corporate Secretary, The AES Corporation, 4300 Wilson Boulevard, Arlington, Virginia 22203. Exhibits also may be requested, but a charge equal to the reproduction cost thereof will be made. A copy of the Annual Report on Form 10-K may be obtained by visiting the Company’s website at www.aes.com.

Website Disclosure

AES uses its website, including its quarterly updates, as channels of distribution of Company information. The information AES posts through these channels may be deemed material. Accordingly, investors should monitor our website, in addition to following AES’ press releases, quarterly SEC filings and public conference calls and webcasts. In addition, you may automatically receive e-mail alerts and other information about AES when you enroll your e-mail address by visiting the “Subscribe to Alerts” page of AES’ Investors website. The contents of AES’ website, including its quarterly updates, are not, however, incorporated by reference into this release.

THE AES CORPORATION Condensed Consolidated Statements of Operations (Unaudited)

	Three Months Ended June 30,		Six Months Ended June 30,
	2025	2024	2025	2024
	(in millions, except share and per share amounts)
Revenue:
Non-Regulated	$ 1,922	$ 2,070	$ 3,863	$ 4,302
Regulated	933	872	1,918	1,725
Total revenue	2,855	2,942	5,781	6,027
Cost of Sales:
Non-Regulated	(1,607)	(1,671)	(3,268)	(3,404)
Regulated	(795)	(718)	(1,619)	(1,451)
Total cost of sales	(2,402)	(2,389)	(4,887)	(4,855)
Operating margin	453	553	894	1,172
General and administrative expenses	(49)	(66)	(126)	(141)
Interest expense	(352)	(389)	(694)	(746)
Interest income	70	88	139	193
Loss on extinguishment of debt	(5)	(9)	(13)	(10)
Other expense	(295)	(84)	(347)	(122)
Other income	31	21	38	56
Gain on disposal and sale of business interests	70	1	69	44
Asset impairment reversals (expense)	154	(38)	105	(84)
Foreign currency transaction gains (losses)	(28)	38	(38)	30
Other non-operating expense	(10)	—	(10)	—
INCOME FROM CONTINUING OPERATIONS BEFORE TAXES AND EQUITY IN EARNINGS OF AFFILIATES	39	115	17	392
Income tax benefit (expense)	(167)	35	(184)	51
Net equity in earnings (losses) of affiliates	(22)	3	(56)	(12)
NET INCOME (LOSS)	(150)	153	(223)	431
Less: Net loss attributable to noncontrolling interests and redeemable stock of subsidiaries	55	123	174	277
NET INCOME (LOSS) ATTRIBUTABLE TO THE AES CORPORATION	$ (95)	$ 276	$ (49)	$ 708
Decrease (increase) in redemption value of redeemable stock of subsidiaries	(10)	6	(10)	—
NET INCOME (LOSS) AVAILABLE TO THE AES CORPORATION COMMON STOCKHOLDERS	$ (105)	$ 282	$ (59)	$ 708
BASIC EARNINGS PER SHARE:
NET INCOME (LOSS) AVAILABLE TO THE AES CORPORATION COMMON STOCKHOLDERS	$ (0.15)	$ 0.40	$ (0.08)	$ 1.01
DILUTED EARNINGS PER SHARE:
NET INCOME (LOSS) AVAILABLE TO THE AES CORPORATION COMMON STOCKHOLDERS	$ (0.15)	$ 0.39	$ (0.08)	$ 0.99
DILUTED SHARES OUTSTANDING	712	713	712	713

THE AES CORPORATION
Strategic Business Unit (SBU) Information
(Unaudited)

	Three Months Ended June 30,		Six Months Ended June 30,
(in millions)	2025	2024	2025	2024
REVENUE
Renewables SBU	$ 644	$ 619	$ 1,310	$ 1,262
Utilities SBU	954	896	1,963	1,769
Energy Infrastructure SBU	1,306	1,462	2,626	3,071
New Energy Technologies SBU	—	—	—	—
Corporate and Other	43	40	79	73
Eliminations	(92)	(75)	(197)	(148)
Total Revenue	$ 2,855	$ 2,942	$ 5,781	$ 6,027

THE AES CORPORATION Condensed Consolidated Balance Sheets (Unaudited)

	June 30, 2025	December 31, 2024
	(in millions, except share and per share data)
ASSETS
CURRENT ASSETS
Cash and cash equivalents	$ 1,350	$ 1,524
Restricted cash	763	437
Accounts receivable, net of allowance of $54 and $52, respectively	1,865	1,646
Inventory	647	593
Prepaid expenses	132	157
Other current assets, net of allowance of $2 and $0, respectively	1,532	1,612
Current held-for-sale assets	31	862
Total current assets	6,320	6,831
NONCURRENT ASSETS
Property, plant and equipment, net of accumulated depreciation of $9,311 and $8,701, respectively	34,727	33,166
Investments in and advances to affiliates	1,091	1,124
Debt service reserves and other deposits	88	78
Goodwill	345	345
Other intangible assets, net of accumulated amortization of $472 and $426, respectively	2,050	1,947
Deferred income taxes	402	365
Loan receivable, net of allowance of $20 and $0, respectively	800	—
Other noncurrent assets, net of allowance of $22 and $20, respectively	2,719	2,917
Noncurrent held-for-sale assets	—	633
Total noncurrent assets	42,222	40,575
TOTAL ASSETS	$ 48,542	$ 47,406
LIABILITIES, REDEEMABLE STOCK OF SUBSIDIARIES, AND EQUITY
CURRENT LIABILITIES
Accounts payable	$ 1,663	$ 1,654
Accrued interest	277	256
Accrued non-income taxes	292	249
Supplier financing arrangements	621	917
Accrued and other liabilities	1,109	1,246
Recourse debt	990	899
Non-recourse debt	2,727	2,688
Current held-for-sale liabilities	—	662
Total current liabilities	7,679	8,571
NONCURRENT LIABILITIES
Recourse debt	4,802	4,805
Non-recourse debt	21,752	20,626
Deferred income taxes	1,635	1,490
Other noncurrent liabilities	2,812	2,881
Noncurrent held-for-sale liabilities	—	391
Total noncurrent liabilities	31,001	30,193
Commitments and Contingencies
Redeemable stock of subsidiaries	2,179	938
EQUITY
THE AES CORPORATION STOCKHOLDERS’ EQUITY
Common stock ($0.01 par value, 1,200,000,000 shares authorized; 859,711,007 issued and 711,922,815 outstanding at June 30, 2025 and 859,709,987 issued and 711,074,269 outstanding at December 31, 2024)	9	9
Additional paid-in capital	6,070	5,913
Retained earnings (accumulated deficit)	(79)	293
Accumulated other comprehensive loss	(836)	(766)
Treasury stock, at cost (147,788,192 and 148,635,718 shares at June 30, 2025 and December 31, 2024, respectively)	(1,795)	(1,805)
Total AES Corporation stockholders’ equity	3,369	3,644
NONCONTROLLING INTERESTS	4,314	4,060
Total equity	7,683	7,704
TOTAL LIABILITIES, REDEEMABLE STOCK OF SUBSIDIARIES, AND EQUITY	$ 48,542	$ 47,406

THE AES CORPORATION Condensed Consolidated Statements of Cash Flows (Unaudited)

	Three Months Ended June 30,		Six Months Ended June 30,
	2025	2024	2025	2024
	(in millions)		(in millions)
OPERATING ACTIVITIES:
Net income (loss)	$ (150)	$ 153	$ (223)	$ 431
Adjustments to net income (loss):
Depreciation, amortization, and accretion of AROs	354	315	691	633
Emissions allowance expense	76	24	178	71
Loss (gain) on realized/unrealized derivatives	86	(64)	71	(137)
Loss on commencement of sales-type leases	199	72	208	67
Gain on disposal and sale of business interests	(70)	(1)	(69)	(44)
Impairment expense (reversals)	(144)	38	(95)	84
Loss on realized/unrealized foreign currency	24	78	24	78
Deferred income tax expense (benefit), net of tax credit transfers allocated to AES	139	36	149	258
Tax credit transfers allocated to noncontrolling interests	212	26	212	26
Other	100	(313)	220	(210)
Changes in operating assets and liabilities:
(Increase) decrease in accounts receivable	125	(7)	26	(239)
(Increase) decrease in inventory	(1)	(41)	(29)	31
(Increase) decrease in prepaid expenses and other current assets	29	94	198	133
(Increase) decrease in other assets	57	138	75	47
Increase (decrease) in accounts payable and other current liabilities	(119)	(75)	(116)	(160)
Increase (decrease) in income tax payables, net and other tax payables	1	(137)	(82)	(464)
Increase (decrease) in other liabilities	58	56	83	74
Net cash provided by operating activities	976	392	1,521	679
INVESTING ACTIVITIES:
Capital expenditures	(1,332)	(1,685)	(2,586)	(3,833)
Acquisitions of business interests, net of cash and restricted cash acquired	(108)	(16)	(112)	(73)
Proceeds from the sale of business interests, net of cash and restricted cash sold	—	—	5	11
Sale of short-term investments	19	393	52	534
Purchase of short-term investments	(18)	(460)	(36)	(604)
Contributions and loans to equity affiliates	—	(29)	(1)	(50)
Purchase of emissions allowances	(195)	(35)	(234)	(91)
Other investing	34	(6)	30	(118)
Net cash used in investing activities	(1,600)	(1,838)	(2,882)	(4,224)
FINANCING ACTIVITIES:
Borrowings under the revolving credit facilities	941	2,262	2,128	4,003
Repayments under the revolving credit facilities	(1,947)	(1,545)	(2,398)	(2,582)
Commercial paper borrowings (repayments), net	(188)	(29)	67	690
Issuance of recourse debt	—	950	800	950
Repayments of recourse debt	—	—	(774)	—
Issuance of non-recourse debt	1,039	1,667	2,332	3,798
Repayments of non-recourse debt	(731)	(1,811)	(1,490)	(2,726)
Payments for financing fees	(28)	(44)	(49)	(75)
Purchases under supplier financing arrangements	250	222	567	708
Repayments of obligations under supplier financing arrangements	(234)	(539)	(862)	(1,055)
Distributions to noncontrolling interests	(254)	(105)	(338)	(128)
Contributions from noncontrolling interests	201	71	274	97
Sales to noncontrolling interests	893	198	1,138	323
Issuance of preferred shares in subsidiaries	444	—	452	—
Dividends paid on AES common stock	(125)	(122)	(250)	(238)
Payments for financed capital expenditures	(14)	(12)	(21)	(19)
Other financing	(102)	(10)	(114)	13
Net cash provided by financing activities	145	1,153	1,462	3,759
Effect of exchange rate changes on cash, cash equivalents and restricted cash	(4)	(28)	(5)	(43)
(Increase) decrease in cash, cash equivalents and restricted cash of held-for-sale businesses	118	(86)	66	(13)
Total increase in cash, cash equivalents and restricted cash	(365)	(407)	162	158
Cash, cash equivalents and restricted cash, beginning	2,566	1,980	2,039	1,990
Cash, cash equivalents and restricted cash, ending	$ 2,201	$ 1,573	$ 2,201	$ 2,148
SUPPLEMENTAL DISCLOSURES:
Cash payments for interest, net of amounts capitalized	$ 331	$ 411	$ 598	$ 765
Cash payments for income taxes, net of refunds	74	141	134	209
SCHEDULE OF NONCASH INVESTING AND FINANCING ACTIVITIES:
Noncash contributions from noncontrolling interests	$ 212	$ 25	$ 254	$ 25
Receivable for proceeds from the sale of Dominican Republic Renewables	100	—	100	—
Noncash recognition of new operating and financing leases	18	56	78	180
Noncash distributions to noncontrolling interests	45	—	45	—
Initial recognition of contingent consideration for acquisitions	11	5	11	14
Conversion of Corporate Units to shares of common stock	—	—	—	838
Liabilities derecognized upon completion of remaining performance obligation for sale of Warrior Run receivables	—	273	—	273

THE AES CORPORATION
NON-GAAP FINANCIAL MEASURES
(Unaudited)
RECONCILIATION OF ADJUSTED EBITDA, ADJUSTED PTC AND ADJUSTED EPS

We define EBITDA as earnings before interest income and expense, taxes, depreciation, amortization, and accretion of AROs. We define Adjusted EBITDA as EBITDA adjusted for the impact of NCI and interest, taxes, depreciation, amortization, and accretion of AROs of our equity affiliates, adding back interest income recognized under service concession arrangements, and excluding gains or losses of both consolidated entities and entities accounted for under the equity method due to (a) unrealized gains or losses pertaining to derivative transactions, equity securities, and financial assets and liabilities measured using the fair value option; (b) unrealized foreign currency gains or losses; (c) gains, losses, benefits and costs associated with dispositions and acquisitions of business interests, including early plant closures, and gains and losses recognized at commencement of sales-type leases; (d) losses due to impairments; (e) gains, losses, and costs due to the early retirement of debt or troubled debt restructuring, and (f) costs directly associated with a major restructuring program, including, but not limited to, workforce reduction efforts. We define Adjusted EBITDA with Tax Attributes as Adjusted EBITDA, adding back the pre-tax effect of Production Tax Credits (“PTCs”), Investment Tax Credits (“ITCs”), and depreciation tax deductions allocated to tax equity investors, as well as the tax benefit recorded from tax credits retained or transferred to third parties.

The GAAP measure most comparable to EBITDA, Adjusted EBITDA, and Adjusted EBITDA with Tax Attributes is net income. We believe that EBITDA, Adjusted EBITDA, and Adjusted EBITDA with Tax Attributes better reflect the underlying business performance of the Company. Adjusted EBITDA is the most relevant measure considered in the Company’s internal evaluation of the financial performance of its segments. Factors in this determination include the variability due to unrealized gains or losses pertaining to derivative transactions, equity securities, or financial assets and liabilities remeasurement, unrealized foreign currency gains or losses, losses due to impairments, strategic decisions to dispose of or acquire business interests, retire debt, or implement restructuring initiatives, and the variability of allocations of earnings to tax equity investors, which affect results in a given period or periods. In addition, each of these metrics represent the business performance of the Company before the application of statutory income tax rates and tax adjustments, including the effects of tax planning, corresponding to the various jurisdictions in which the Company operates. EBITDA, Adjusted EBITDA, and Adjusted EBITDA with Tax Attributes should not be construed as alternatives to net income, which is determined in accordance with GAAP.

	Three Months Ended June 30,		Six Months Ended June 30,
Reconciliation of Adjusted EBITDA and Adjusted EBITDA with Tax Attributes (in millions)	2025	2024	2025	2024
Net income (loss)	$ (150)	$ 153	$ (223)	$ 431
Income tax expense (benefit)	167	(35)	184	(51)
Interest expense	352	389	694	746
Interest income	(70)	(88)	(139)	(193)
Depreciation, amortization, and accretion of AROs	354	315	691	633
EBITDA	$ 653	$ 734	$ 1,207	$ 1,566
Less: Adjustment for noncontrolling interests and redeemable stock of subsidiaries ⁽¹⁾	(253)	(182)	(387)	(346)
Less: Income tax expense (benefit), interest expense (income) and depreciation, amortization, and accretion of AROs from equity affiliates	45	28	81	62
Interest income recognized under service concession arrangements	14	16	29	33
Unrealized derivatives, equity securities, and financial assets and liabilities losses (gains)	133	(53)	132	(138)
Unrealized foreign currency losses (gains)	4	12	(3)	3
Disposition/acquisition losses	126	62	167	19
Impairment losses (reversals)	(87)	23	(54)	49
Loss on extinguishment of debt and troubled debt restructuring	4	18	12	50
Restructuring costs	42	—	88	—
Adjusted EBITDA ⁽¹⁾	$ 681	$ 658	$ 1,272	$ 1,298
Tax attributes	376	191	562	419
Adjusted EBITDA with Tax Attributes ⁽²⁾	$ 1,057	$ 849	$ 1,834	$ 1,717


⁽¹⁾	The allocation of earnings and losses to tax equity investors from both consolidated entities and equity affiliates is removed from Adjusted EBITDA. NCI also excludes amounts allocated to preferred shareholders during the construction phase before a project becomes operational, as this is akin to a financing arrangement.
⁽²⁾	Adjusted EBITDA with Tax Attributes includes the impact of the share of the ITCs, PTCs, and depreciation deductions allocated to tax equity investors under the HLBV accounting method and recognized as Net loss (income) attributable to noncontrolling interests and redeemable stock of subsidiaries on the Condensed Consolidated Statements of Operations. It also includes the tax benefit recorded from tax credits retained or transferred to third parties. The tax attributes are related to the Renewables and Utilities SBUs.

We define Adjusted PTC as pre-tax income from continuing operations attributable to The AES Corporation excluding gains or losses of the consolidated entity due to (a) unrealized gains or losses pertaining to derivative transactions, equity securities, and financial assets and liabilities measured using the fair value option; (b) unrealized foreign currency gains or losses; (c) gains, losses, benefits, and costs associated with dispositions and acquisitions of business interests, including early plant closures, and gains and losses recognized at commencement of sales-type leases; (d) losses due to impairments; (e) gains, losses, and costs due to the early retirement of debt or troubled debt restructuring; and (f) costs directly associated with a major restructuring program, including, but not limited to, workforce reduction efforts. Adjusted PTC also includes net equity in earnings of affiliates on an after-tax basis adjusted for the same gains or losses excluded from consolidated entities.

We define Adjusted EPS as diluted earnings per share from continuing operations excluding gains or losses of both consolidated entities and entities accounted for under the equity method due to (a) unrealized gains or losses pertaining to derivative transactions, equity securities, and financial assets and liabilities measured using the fair value option; (b) unrealized foreign currency gains or losses; (c) gains, losses, benefits and costs associated with dispositions and acquisitions of business interests, including early plant closures, and the tax impact from the repatriation of sales proceeds, and gains and losses recognized at commencement of sales-type leases; (d) losses due to impairments; (e) gains, losses, and costs due to the early retirement of debt or troubled debt restructuring; and (f) costs directly associated with a major restructuring program, including, but not limited to, workforce reduction efforts.

The GAAP measure most comparable to Adjusted PTC is income from continuing operations attributable to AES. The GAAP measure most comparable to Adjusted EPS is diluted earnings per share from continuing operations. We believe that Adjusted PTC and Adjusted EPS better reflect the underlying business performance of the Company and are considered in the Company’s internal evaluation of financial performance. Factors in this determination include the variability due to unrealized gains or losses pertaining to derivative transactions, equity securities, or financial assets and liabilities remeasurement, unrealized foreign currency gains or losses, losses due to impairments, and strategic decisions to dispose of or acquire business interests, retire debt, or implement restructuring initiatives, which affect results in a given period or periods. In addition, for Adjusted PTC, earnings before tax represents the business performance of the Company before the application of statutory income tax rates and tax adjustments, including the effects of tax planning, corresponding to the various jurisdictions in which the Company operates. Adjusted PTC and Adjusted EPS should not be construed as alternatives to income from continuing operations attributable to AES and diluted earnings per share from continuing operations, which are determined in accordance with GAAP.

The Company reported diluted loss per share of $0.15 and $0.08 for the three and six months ended June 30, 2025. The Company reported diluted earnings per share of $0.39 and $0.99 for the three and six months ended June 30, 2024. For purposes of measuring earnings per share under U.S. GAAP, income available to AES common stockholders is reduced by increases in the carrying amount of redeemable stock of subsidiaries to redemption value and increased by decreases in the carrying amount to the extent they represent recoveries of amounts previously reflected in the computation of earnings per share. While the adjustment for the three and six months ended June 30, 2025 decreased earnings per share and the adjustment for the three months ended June 30, 2024 increased earnings per share, neither adjustment impacted Net income on the Condensed Consolidated Statement of Operations. For purposes of computing Adjusted EPS, the Company excluded the adjustment to redemption value from the numerator. The table below reconciles the income available to AES common stockholders used in GAAP diluted earnings per share to the income from continuing operations used in calculating the non-GAAP measure of Adjusted EPS.

Reconciliation of Numerator Used for Adjusted EPS	Three months ended June 30, 2025			Six months ended June 30, 2025
(in millions, except per share data)	Loss	Shares	$ per Share	Loss	Shares	$ per Share
GAAP DILUTED LOSS PER SHARE
Loss available to The AES Corporation common stockholders	$ (105)	712	$ (0.15)	$ (59)	712	$ (0.08)
Add back: Adjustment to redemption value of redeemable stock of subsidiaries	10	—	0.02	10	—	0.01
NON-GAAP DILUTED LOSS PER SHARE BEFORE EFFECT OF DILUTIVE SECURITIES	$ (95)	712	$ (0.13)	$ (49)	712	$ (0.07)
Restricted stock units	—	2	—	—	1	—
NON-GAAP DILUTED LOSS PER SHARE	$ (95)	714	$ (0.13)	$ (49)	713	$ (0.07)


Reconciliation of Numerator Used for Adjusted EPS	Three months ended June 30, 2024			Six months ended June 30, 2024
(in millions, except per share data)	Income	Shares	$ per Share	Income	Shares	$ per Share
GAAP DILUTED EARNINGS PER SHARE
Income available to The AES Corporation common stockholders	$ 282	713	$ 0.39	$ 708	713	$ 0.99
Add back: Adjustment to redemption value of redeemable stock of subsidiaries	(6)	—	—	—	—	—
NON-GAAP DILUTED EARNINGS PER SHARE	$ 276	713	$ 0.39	$ 708	713	$ 0.99

	Three Months Ended June 30, 2025			Three Months Ended June 30, 2024			Six Months Ended June 30, 2025			Six Months Ended June 30, 2024
	Net of NCI ⁽¹⁾	Per Share (Diluted) Net of NCI ⁽¹⁾		Net of NCI ⁽¹⁾	Per Share (Diluted) Net of NCI ⁽¹⁾		Net of NCI ⁽¹⁾	Per Share (Diluted) Net of NCI ⁽¹⁾		Net of NCI ⁽¹⁾	Per Share (Diluted) Net of NCI ⁽¹⁾
	(in millions, except per share amounts)
Income (loss) from continuing operations, net of tax, attributable to AES and Diluted EPS	$ (95)	$ (0.13)		$ 276	$ 0.39		$ (49)	$ (0.07)		$ 708	$ 0.99
Add: Income tax expense (benefit) from continuing operations attributable to AES	148			(67)			144			(86)
Pre-tax contribution	$ 53			$ 209			$ 95			$ 622
Adjustments
Unrealized derivatives, equity securities, and financial assets and liabilities losses (gains)	$ 133	$ 0.18	(2)	$ (53)	$ (0.07)	(3)	$ 128	$ 0.19	(4)	$ (138)	$ (0.19)	(5)
Unrealized foreign currency losses (gains)	4	—		12	0.01		(3)	—		3	—
Disposition/acquisition losses	125	0.18	(6)	62	0.08	(7)	167	0.23	(8)	19	0.03	(9)
Impairment losses (reversals)	(87)	(0.12)	(10)	23	0.03	(11)	(54)	(0.08)	(12)	49	0.08	(13)
Loss on extinguishment of debt and troubled debt restructuring	6	0.01		20	0.03	(14)	16	0.02		54	0.07	(15)
Restructuring costs	42	0.06	(16)	—	—		88	0.12	(17)	—	—
Less: Net income tax expense (benefit)		0.33	(18)		(0.09)	(19)		0.37	(20)		(0.09)	(19)
Adjusted PTC and Adjusted EPS	$ 276	$ 0.51		$ 273	$ 0.38		$ 437	$ 0.78		$ 609	$ 0.89


⁽¹⁾	NCI is defined as Noncontrolling Interests.
⁽²⁾	Amount primarily relates to remeasurement of our investment in 5B of $48 million, or $0.07 per share, net unrealized derivative losses at the Energy Infrastructure SBU of $38 million, or $0.05 per share, and unrealized derivative losses on commodities at AES Clean Energy of $33 million, or $0.05 per share.
⁽³⁾	Amount primarily relates to unrealized gains on foreign currency derivatives at Corporate of $34 million, or $0.05 per share, and unrealized gains on cross currency swaps in Brazil of $25 million, or $0.03 per share.
⁽⁴⁾	Amount primarily relates to remeasurement of our investment in 5B of $48 million, or $0.07 per share, net unrealized derivative losses at the Energy Infrastructure SBU of $46 million, or $0.06 per share, and unrealized derivative losses on commodities at AES Clean Energy of $17 million, or $0.02 per share.
⁽⁵⁾	Amount primarily relates to net unrealized derivative gains at the Energy Infrastructure SBU of $59 million, or $0.08 per share, unrealized gains on foreign currency derivatives at Corporate of $37 million, or $0.05 per share, and unrealized gains on cross currency swaps in Brazil of $28 million, or $0.04 per share.
⁽⁶⁾	Amount primarily relates to day-one losses on commencement of sales-type leases at AES Clean Energy Development of $149 million, or $0.21 per share, partially offset by gain on sale of Dominican Republic Renewables of $45 million, or $0.06 per share.
⁽⁷⁾	Amount primarily relates to day-one losses at commencement of sales-type leases at AES Renewable Holdings of $63 million, or $0.09 per share.
⁽⁸⁾	Amount primarily relates to day-one losses on commencement of sales-type leases at AES Clean Energy Development of $149 million, or $0.21 per share, and AES Renewable Holdings of $9 million, or $0.01 per share, and losses on remeasurement of contingent consideration at AES Clean Energy of $12 million, or $0.02 per share, partially offset by gain on sale of Dominican Republic Renewables of $45 million, or $0.06 per share.
⁽⁹⁾	Amount primarily relates to day-one losses at commencement of sales-type leases at AES Renewable Holdings of $63 million, or $0.09 per share, and the loss on partial sale of our ownership interest in Amman East and IPP4 in Jordan of $10 million, or $0.01 per share, partially offset by a gain on dilution of ownership in Uplight due to its acquisition of AutoGrid of $52 million, or $0.07 per share.
⁽¹⁰⁾	Amount primarily relates to the derecognition of the valuation allowance on a loan receivable accounted for under ASC 310 and the elimination of estimated costs to sell at Mong Duong of $127 million, or $0.18 per share, after reclassification to held and used, partially offset by impairments at AES Clean Energy of $29 million, or $0.04 per share.
⁽¹¹⁾	Amount primarily relates to impairment at AES Brasil of $12 million, or $0.02 per share.
⁽¹²⁾	Amount primarily relates to the derecognition of the valuation allowance on a loan receivable accounted for under ASC 310 and the elimination of estimated costs to sell at Mong Duong of $127 million, or $0.18 per share, after reclassification to held and used, partially offset by impairments at AES Clean Energy of $54 million, or $0.08 per share, and at Mong Duong of $9 million, or $0.01 per share.
⁽¹³⁾	Amount primarily relates to impairment at Mong Duong of $22 million, or $0.03 per share, and impairment at AES Brasil of $12 million, or $0.02 per share.
⁽¹⁴⁾	Amount primarily relates to losses incurred at AES Andes due to early retirement of debt of $16 million, or $0.02 per share.
⁽¹⁵⁾	Amount primarily relates to losses incurred at AES Andes due to early retirement of debt $29 million, or $0.04 per share, and costs incurred due to troubled debt restructuring at Puerto Rico of $20 million, or $0.03 per share.
⁽¹⁶⁾	Amount primarily relates to impairments at AES Clean Energy Development that were the result of the Company-wide restructuring program of $38 million, or $0.05 per share.
⁽¹⁷⁾	Amount primarily relates to severance costs associated with the Company-wide restructuring program of $50 million, or $0.07 per share, and impairments at AES Clean Energy Development that were the result of the Company’s restructuring program of $38 million, or $0.05 per share.
⁽¹⁸⁾	Amount primarily relates to income tax expense associated with the day-one losses on commencement of sales-type leases at AES Clean Energy Development of $95 million, or $0.13 per share, impairments at AES Clean Energy Development of $50 million, or $0.07 per share, remeasurement and downward adjustment of our investment in 5B of $28 million, or $0.04 per share, the selldown of AES Ohio of $13 million, or $0.02 per share, and net unrealized derivative losses at Integrated Energy of $18 million, or $0.03 per share.
⁽¹⁹⁾	Amount primarily relates to income tax benefits associated with the tax over book investment basis differences related to the AES Brasil held-for-sale classification of $59 million, or $0.08 per share, for the three and six months ended June 30, 2024.
⁽²⁰⁾	Amount primarily relates to income tax expense associated with the day-one losses on commencement of sales-type leases at AES Clean Energy Development of $95 million, or $0.13 per share, impairments at AES Clean Energy Development of $57 million, or $0.08 per share, severance costs related to the Company-wide restructuring program of $23 million, or $0.03 per share, remeasurement and downward adjustment of our investment in 5B of $28 million, or $0.04 per share, net unrealized derivative losses at Integrated Energy of $19 million, or $0.03 per share, and the selldown of AES Ohio of $13 million, or $0.02 per share.

The AES Corporation
Parent Financial Information
Parent only data: last four quarters
(in millions)	4 Quarters Ended
Total subsidiary distributions & returns of capital to Parent	June 30, 2025	March 31, 2025	December 31, 2024	September 30, 2024
	Actual	Actual	Actual	Actual
Subsidiary distributions⁽¹⁾ to Parent & QHCs	$ 1,706	$ 1,447	$ 1,603	$ 1,424
Returns of capital distributions to Parent & QHCs	75	32	30	80
Total subsidiary distributions & returns of capital to Parent	$ 1,781	$ 1,479	$ 1,633	$ 1,504
Parent only data: quarterly
(in millions)	Quarter Ended
Total subsidiary distributions & returns of capital to Parent	June 30, 2025	March 31, 2025	December 31, 2024	September 30, 2024
	Actual	Actual	Actual	Actual
Subsidiary distributions¹ to Parent & QHCs	$ 557	$ 230	$ 715	$ 204
Returns of capital distributions to Parent & QHCs	44	3	28	—
Total subsidiary distributions & returns of capital to Parent	$ 601	$ 233	$ 743	$ 204

(in millions)	Balance at
	June 30, 2025	March 31, 2025	December 31, 2024	September 30, 2024
Parent Company Liquidity⁽²⁾	Actual	Actual	Actual	Actual
Cash at Parent & Cash at QHCs⁽³⁾	$ 9	$ 151	$ 265	$ 6
Availability under credit facilities	2,185	1,526	1,782	335
Ending liquidity	$ 2,194	$ 1,677	$ 2,047	$ 341


⁽¹⁾	Subsidiary distributions received by Qualified Holding Companies (“QHCs”) excluded from Schedule 1. Subsidiary Distributions should not be construed as an alternative to Consolidated Net Cash Provided by Operating Activities, which is determined in accordance with US GAAP. Subsidiary Distributions are important to the Parent Company because the Parent Company is a holding company that does not derive any significant direct revenues from its own activities but instead relies on its subsidiaries’ business activities and the resultant distributions to fund the debt service, investment and other cash needs of the holding company. The reconciliation of the difference between the Subsidiary Distributions and Consolidated Net Cash Provided by Operating Activities consists of cash generated from operating activities that is retained at the subsidiaries for a variety of reasons which are both discretionary and non-discretionary in nature. These factors include, but are not limited to, retention of cash to fund capital expenditures at the subsidiary, cash retention associated with non-recourse debt covenant restrictions and related debt service requirements at the subsidiaries, retention of cash related to sufficiency of local GAAP statutory retained earnings at the subsidiaries, retention of cash for working capital needs at the subsidiaries, and other similar timing differences between when the cash is generated at the subsidiaries and when it reaches the Parent Company and related holding companies.
⁽²⁾	Parent Company Liquidity is defined as cash available to the Parent Company, including cash at qualified holding companies (QHCs), plus available borrowings under our existing credit facility. AES believes that unconsolidated Parent Company liquidity is important to the liquidity position of AES as a Parent Company because of the non-recourse nature of most of AES’ indebtedness.
⁽³⁾	The cash held at QHCs represents cash sent to subsidiaries of the company domiciled outside of the US. Such subsidiaries have no contractual restrictions on their ability to send cash to AES, the Parent Company. Cash at those subsidiaries was used for investment and related activities outside of the US. These investments included equity investments and loans to other foreign subsidiaries as well as development and general costs and expenses incurred outside the US. Since the cash held by these QHCs is available to the Parent, AES uses the combined measure of subsidiary distributions to Parent and QHCs as a useful measure of cash available to the Parent to meet its international liquidity needs.

Investor Contact: Susan Harcourt 703-682-1204, [email protected]
Media Contact: Amy Ackerman 703-682-6399, [email protected]

SOURCE The AES Corporation

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July 31, 2025

Category: 3. Business

Lundin Mining Announces Updated Share Capital and Provides Update on Share Buybacks

Sources: Barnichon (2010), Petrosky-Nadeau and Zhang (2021), and Bureau of Labour Statistics.

Notes: The figure displays the mean and standard deviation of the detection errors for 2,343,752 perfect classifiers, which detect the 15 recessions that occurred between 1929 and 2021 without false positives.

Notes: The probability is the average of the probabilities given by the individual classifiers in the ensemble (thin orange lines). The classifiers in the ensemble are selected from the high-precision segment of the 1929–2021 anticipation-precision frontier.

Notes: The probability is the average of the probabilities given by the individual classifiers in the ensemble (thin orange lines). The classifiers in the ensemble are selected from the high-precision segment of the 1929–1984 anticipation-precision frontier.

References

References