Trump's stooge has a crazy plan to weaken the dollar
Already, Donald Trump has shattered post-war convention by imposing some of the highest tariffs since the notorious Smoot-Hawley Tariff Act of 1930.
It goes without saying that a weaker dollar furthers Trump's protectionist goals by making imports more expensive and exports cheaper.
And now he's alighted on just the man who might help bring that devaluation about – Stephen Miran, the chairman of the council of economic advisers.
Miran has been nominated by Trump for a soon-to-be-vacated seat on the Federal Reserve's board of governors, and is therefore considered to be a prime candidate to replace Jerome Powell as chairman when the incumbent's term ends in May next year – or possibly sooner, if Trump gets his way in forcing the incumbent's early resignation.
There are lots of other names in the frame, so Miran cannot yet regard himself as a shoo-in for the job. But in some respects at least, he sings from the same hymn sheet as Trump, so he's in with a decent chance.
Miran is a committed 'devaluationist', and once appointed head of the world's most powerful monetary authority, could steer policy decisively in the direction of a weaker dollar.
Does it make any kind of sense? As on most other aspects of Trump's economic agenda, the President's 'vision' for the dollar is a mass of contradictions and apparently incompatible goals.
He wants both a weaker dollar so as to make American goods more competitive and thereby reduce the trade deficit. But at the same time, he wants to preserve and enhance the dollar's global reserve currency status, and its parallel position as the predominant international means of exchange.
To list but the most important of them, the benefits of dollar hegemony include enabling the US to borrow more cheaply in world markets, the exercise of geo-political influence through the imposition of sanctions, and encouraging foreign investment in the US.
It is not at all clear that Trump can maintain what France's one-time president, Valéry Giscard d'Estaing, called America's 'exorbitant privilege' while at the same time pursuing strategies, such as inflationary monetary policy, that might weaken its currency.
We know what Miran's thoughts on the matter are, since he wrote about them in a paper published shortly before Trump's re-election as president. His musings might be seen as an extended job application.
The dollar has long been persistently overvalued from a trade perspective, he argued, and that's in large part because dollar assets 'function as the world's reserve currency'.
Can you have one without the other, both reserve currency supremacy and a much weaker dollar?
Not according to Miran, who suggests that foreigners could be taxed on their holdings of US Treasuries to lessen their attractions to overseas investors, never mind that this would be both a technical and legal default.
If that happened, then the dollar would indeed lose the commanding position it now holds; it's hard to imagine a policy less likely to make America great again, and essentially amounts to quack economics.
As it happens, Trump already seems to be getting his way on a weaker dollar, and that's without even trying. Conventional economics would suggest that if you raise tariffs significantly, the dollar would appreciate to compensate, negating at least part of the impact of tariffs on prices.
In the event, it's actually gone the other way, depreciating by nearly 10pc on a trade-weighted basis since it first became apparent that Trump was deadly serious about tariffs.
Hashtags
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Geeky Gadgets
16 minutes ago
- Geeky Gadgets
Create Ads Like a Pro : How AI Is Transforming Modern Marketing
What if your next ad campaign could be created in minutes, tailored to your audience, and optimized in real time—all without a single brainstorming session? This isn't a distant future; it's the reality of AI in advertising. From generating stunning visuals to analyzing audience behavior with pinpoint accuracy, artificial intelligence is transforming how brands connect with consumers. Yet, as innovative as it sounds, this shift raises an important question: can algorithms truly replace the emotional depth and creativity that make great advertising unforgettable? The answer lies not in choosing between AI and human ingenuity, but in discovering how they can work together to redefine what's possible. In this breakdown, Marketing Against the Grain explore the fascinating intersection of AI-driven efficiency and human creativity, uncovering how brands are using innovative technologies like diffusion models and reinforcement learning to scale content production and optimize campaigns. You'll learn how AI can analyze trends, localize ads for diverse audiences, and even refine its own outputs in real time. But we'll also examine the challenges—like maintaining cultural relevance and ethical integrity—that come with relying on machines for creative work. Whether you're a marketer, a creative professional, or simply curious about the future of advertising, this exploration will leave you questioning not just how ads are made, but what makes them truly resonate. AI's Impact on Advertising How AI is Transforming Content Creation AI has become an indispensable tool in modern advertising, significantly reducing the time and cost associated with creating campaigns. Its ability to ideate, design, and distribute content across multiple platforms gives brands a competitive edge in today's fast-paced digital environment. Key capabilities of AI in content creation include: Audience Analysis: AI can analyze audience preferences and behaviors to generate tailored ad campaigns that maximize engagement and relevance. AI can analyze audience preferences and behaviors to generate tailored ad campaigns that maximize engagement and relevance. Real-Time Optimization: By monitoring metrics such as click-through rates and conversion rates, AI refines campaigns in real time to improve performance. Despite these strengths, AI-generated content often faces challenges in maintaining brand consistency and cultural relevance. For example, while AI can mimic a brand's tone, it may struggle to capture the emotional depth or nuanced storytelling required for impactful advertising. This underscores the importance of human oversight to ensure AI outputs align with brand values and resonate with diverse audiences. Why Human Creativity Remains Essential While AI enhances efficiency and scalability, it cannot replicate the originality and emotional intelligence that are hallmarks of effective advertising. Human creativity remains critical in areas such as: Ideation and Storytelling: Crafting compelling narratives requires cultural awareness and emotional nuance, which AI cannot fully replicate. Crafting compelling narratives requires cultural awareness and emotional nuance, which AI cannot fully replicate. Editing and Refinement: Human creators play a vital role in refining AI-generated concepts to ensure they resonate with diverse audiences and avoid cultural insensitivity. Rather than replacing human input, AI serves as a collaborative tool that automates repetitive tasks and provides data-driven insights. This partnership allows human creators to focus on strategic thinking and storytelling, elevating the overall quality of advertising. By combining AI's efficiency with human ingenuity, brands can create campaigns that are both impactful and emotionally engaging. Creating AI Adverts Watch this video on YouTube. Take a look at other insightful guides from our broad collection that might capture your interest in AI in Advertising. Technical Innovations Driving AI in Advertising Recent advancements in AI technology have enabled more sophisticated applications in advertising, pushing the boundaries of what is possible. Key innovations include: Diffusion Models: These models generate highly detailed visuals, enhancing the quality and appeal of ad content. These models generate highly detailed visuals, enhancing the quality and appeal of ad content. Reinforcement Learning: Algorithms that adapt to specific brand guidelines, making sure campaigns align with a brand's identity and objectives. Algorithms that adapt to specific brand guidelines, making sure campaigns align with a brand's identity and objectives. In-Context Learning: AI systems trained on brand-specific data to produce content that reflects a brand's unique voice and style. While these technologies offer significant benefits, they also come with challenges. Training AI models requires extensive data and computational resources, which can be both costly and time-consuming. Additionally, making sure that AI-generated content adheres to ethical standards and avoids biases is an ongoing concern. Brands must carefully evaluate these factors when integrating AI into their advertising strategies to maximize its potential while mitigating risks. Scaling Content Production with AI As the demand for personalized and high-quality content continues to grow, AI provides a scalable solution for brands looking to expand their reach. Its capabilities include: Mass Content Generation: AI can produce large volumes of content tailored to different platforms, demographics, and consumer preferences. AI can produce large volumes of content tailored to different platforms, demographics, and consumer preferences. Localized Campaigns: By accounting for cultural nuances, AI enables the creation of localized advertisements that resonate with specific audiences. By accounting for cultural nuances, AI enables the creation of localized advertisements that resonate with specific audiences. Trend Analysis: AI can identify emerging trends by analyzing social media activity and consumer behavior, helping brands stay ahead of market shifts. This adaptability allows brands to maintain a consistent presence across multiple channels while responding to evolving audience needs. By using AI, advertisers can efficiently scale their operations without compromising on quality or relevance. Balancing Creativity with Data-Driven Insights One of the most significant challenges in AI-driven advertising is striking the right balance between creativity and data-driven optimization. While metrics such as cost-per-thousand impressions (CPM) and conversion rates are essential for measuring campaign success, an over-reliance on these metrics can lead to formulaic content that lacks emotional depth and originality. To address this, brands should adopt a hybrid approach: Use AI for Optimization: Use AI to optimize ad placement, timing, and targeting, making sure campaigns reach the right audience at the right time. Use AI to optimize ad placement, timing, and targeting, making sure campaigns reach the right audience at the right time. Prioritize Human Creativity: Rely on human creators to craft compelling narratives and emotionally resonant content that connects with audiences on a deeper level. This approach ensures that advertising remains both effective and meaningful, combining the precision of AI with the emotional resonance of human creativity. By integrating data-driven insights with creative storytelling, brands can achieve a harmonious balance that drives engagement and builds lasting connections with their audiences. Ethical Considerations in AI-Generated Content The use of AI in advertising raises important ethical considerations that brands must address to maintain trust and integrity. For example, generating realistic images of people without their consent or using AI to manipulate consumer behavior can lead to legal and reputational risks. To navigate these challenges, brands should: Adhere to Ethical Guidelines: Ensure that AI-generated content complies with ethical standards, avoiding deceptive or exploitative practices. Ensure that AI-generated content complies with ethical standards, avoiding deceptive or exploitative practices. Align with Brand Values: Use AI to promote initiatives that reflect the brand's core values, such as sustainability or social responsibility. By integrating ethical considerations into their AI strategies, brands can build trust with their audiences and demonstrate their commitment to responsible innovation. This not only safeguards their reputation but also strengthens their relationship with consumers in an increasingly values-driven marketplace. The Future of AI in Advertising AI is poised to play an increasingly central role in the future of advertising, allowing brands to produce high-quality, targeted content at scale. However, its limitations highlight the enduring importance of human creativity in crafting original and impactful campaigns. By combining AI's efficiency with human ingenuity, brands can navigate the complexities of modern advertising while staying true to their values. As the industry continues to evolve, the collaboration between humans and AI will unlock new possibilities, driving innovation and shaping the future of content creation and marketing. Media Credit: Marketing Against the Grain Filed Under: AI, Guides Latest Geeky Gadgets Deals Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.
Geeky Gadgets
16 minutes ago
- Geeky Gadgets
Excel Trick For Ranking Values for Accurate Data Analysis : Dense Ranking
Have you ever found yourself frustrated by Excel's inability to handle ties in rankings without creating gaps in the sequence? Imagine analyzing employee salaries or sales performance, only to discover that identical values are ranked inconsistently, throwing off your entire report. This is where the concept of dense ranking comes to the rescue. Unlike standard ranking methods, which often leave gaps after ties, dense ranking ensures that identical values share the same rank while maintaining a seamless ranking order. It's a small tweak with a big impact, offering clarity and fairness in your data analysis. In this guide, Chandoo explains a step-by-step approach to mastering dense ranking in Excel, using powerful functions like `LET`, `UNIQUE`, and `FILTER`. Whether you're tackling performance evaluations, sales reports, or any dataset riddled with duplicate values, these techniques will help you create rankings that are both accurate and intuitive. Along the way, you'll also learn how to retrieve associated data effortlessly and even implement dense ranking without adding extra columns. By the end, you'll not only streamline your workflow but also gain a deeper understanding of how to make Excel work smarter for you. Excel Dense Ranking Guide Understanding Dense Ranking Dense ranking assigns the same rank to identical values and ensures no gaps in the ranking sequence. For example, if two entries share the first rank, the next unique value is ranked second, not third. This approach differs from standard ranking, where gaps appear after ties. Dense ranking is particularly useful in scenarios such as: Salary Analysis: Making sure employees with tied salaries are ranked equally without inconsistencies. Making sure employees with tied salaries are ranked equally without inconsistencies. Performance Evaluations: Accurately ranking individuals or teams with identical scores. Accurately ranking individuals or teams with identical scores. Sales Reporting: Identifying top-performing products or regions without misrepresenting tied results. By addressing ties effectively, dense ranking provides a more accurate representation of your data, making it an essential tool for various analytical tasks. Limitations of Standard Ranking Excel's built-in ranking functions, such as `LARGE` or `RANK`, often fall short when handling duplicate values. For instance, if two employees have the same salary, these functions assign them different ranks, leaving gaps in the sequence. This creates inconsistencies, especially in datasets where ties are common. Dense ranking eliminates this issue by making sure that tied values share the same rank while maintaining a continuous ranking sequence. Excel Trick For Ranking Values Watch this video on YouTube. Expand your understanding of Excel functions with additional resources from our extensive library of articles. Step-by-Step Guide to Creating a Dense Rank Column To implement dense ranking in Excel, you can use a combination of powerful functions. Follow these steps to create a dense rank column: Define Variables with `LET`: Use the `LET` function to define and reuse variables within your formula. This improves readability and reduces redundancy. For example, you can store a range of values or intermediate calculations as variables. Use the function to define and reuse variables within your formula. This improves readability and reduces redundancy. For example, you can store a range of values or intermediate calculations as variables. Extract Unique Values with `UNIQUE`: The `UNIQUE` function identifies distinct values in your dataset, grouping duplicate entries together for ranking purposes. The function identifies distinct values in your dataset, grouping duplicate entries together for ranking purposes. Assign Ranks with `FILTER` and `COUNT`: Combine `FILTER` to isolate values and `COUNT` to determine their rank within the unique list. This ensures accurate ranking even when duplicate values are present. For example, in a dataset of employee salaries, you can create a dense rank column that assigns the same rank to employees with identical salaries. This approach ensures fairness and consistency in your analysis. Retrieving Data Using Dense Rank Once you've established a dense rank system, retrieving associated data becomes straightforward. Here are two key functions to simplify this process: Use `XLOOKUP` for Precise Data Retrieval: The `XLOOKUP` function allows you to find corresponding data, such as employee names or departments, based on their rank. This is particularly useful for associating ranks with specific entries in your dataset. The function allows you to find corresponding data, such as employee names or departments, based on their rank. This is particularly useful for associating ranks with specific entries in your dataset. Handle Multiple Matches with `FILTER` and `TEXTJOIN`: When multiple entries share the same rank, `FILTER` can extract all matching values. You can then use `TEXTJOIN` to combine these values into a single cell, separated by commas, for better readability. For instance, if two employees share the first rank, you can use `FILTER` to list their names and `TEXTJOIN` to display them in a single cell. This method ensures that all relevant data is captured and presented clearly. Dense Ranking Without Adding Extra Columns In some cases, you may prefer not to add a dedicated dense rank column to your dataset. Instead, you can calculate ranks directly within a formula. By combining `LET`, `UNIQUE`, and `LARGE`, you can determine ranks and retrieve associated data in a single step. This approach is ideal for one-time analyses or compact datasets where adding extra columns isn't practical. It allows you to maintain a clean and organized worksheet while still using the benefits of dense ranking. Practical Applications of Dense Ranking Dense ranking has a wide range of applications across various fields. Some of the most common use cases include: Performance Analysis: Rank employees, students, or teams based on scores while addressing ties accurately. This ensures fair evaluations and meaningful comparisons. Rank employees, students, or teams based on scores while addressing ties accurately. This ensures fair evaluations and meaningful comparisons. Sales Reporting: Identify top-performing products, regions, or sales representatives without misrepresenting tied results. Dense ranking provides a clear and accurate picture of performance metrics. Identify top-performing products, regions, or sales representatives without misrepresenting tied results. Dense ranking provides a clear and accurate picture of performance metrics. Data Filtering and Retrieval: Extract specific ranks and their associated data efficiently for reporting or decision-making. This is particularly useful in large datasets where precision is critical. By using dense ranking, you can enhance the accuracy and reliability of your data analysis, making it a valuable tool for professionals in various industries. Optimizing Your Workflow with Dense Ranking Dense ranking is a powerful technique for handling duplicate values in Excel. By using functions like `LET`, `UNIQUE`, `FILTER`, `LARGE`, `XLOOKUP`, and `TEXTJOIN`, you can create efficient workflows that accurately rank data and retrieve associated information. Whether you're analyzing salaries, performance metrics, or sales figures, these methods empower you to work smarter and achieve precise results. Incorporating dense ranking into your Excel toolkit can significantly improve the quality and clarity of your data analysis. Media Credit: Chandoo Filed Under: Guides Latest Geeky Gadgets Deals Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.
The Independent
17 minutes ago
- The Independent
Trump's new commercial spaceflight order could benefit Musk's SpaceX
President Donald Trump has signed an executive order to streamline federal oversight of commercial rocket launches, a move that could benefit Elon Musk 's SpaceX and other private space ventures. The White House confirmed the order mandates, among other things, the U.S. transportation secretary to either eliminate or expedite environmental reviews for launch licenses administered by the Federal Aviation Administration. The declaration also calls on the secretary to do away with "outdated, redundant or overly restrictive rules for launch and reentry vehicles." "Inefficient permitting processes discourage investment and innovation, limiting the ability of U.S. companies to lead in global space markets," the executive order states. While Musk and Trump had a high-profile falling out months ago, the billionaire entrepreneur's SpaceX rocket and satellite venture potentially stands to be the single biggest immediate beneficiary of Trump's order on Wednesday. SpaceX, though not mentioned by name in Trump's order, easily leads all U.S. space industry entities, including Nasa, in the sheer number of launches it routinely conducts for its own satellite network, the U.S. space agency, the Pentagon, and other enterprises. Jeff Bezos ' private rocket company, Blue Origin, and its space tourism business could also gain from a more relaxed regulatory regime. Musk has repeatedly complained that environmental impact studies, post-flight mishap investigations and licensing reviews required by the FAA have needlessly slowed testing of SpaceX's Starship rocket, under development at the company's South Texas launch facility. Starship is the centerpiece of Musk's long-term SpaceX business model, as well as a core component of Nasa's ambitions for returning astronauts to the moon's surface, establishing a permanent human lunar presence and ultimately sending crewed missions to Mars. Musk has viewed FAA oversight as a hindrance to his company's engineering culture, considered more risk-tolerant than many of the aerospace industry's more established players. SpaceX's flight-test strategy is known for pushing spacecraft prototypes to the point of failure, then fine-tuning improvements through frequent repetition. This has appeared to run afoul at times with the FAA's mission of safeguarding the public and the environment as it exercises its regulatory jurisdiction over commercial spaceflight. Earlier this year, the FAA grounded Starship test flights for nearly two months after back-to-back post-launch explosions rained debris over Caribbean islands and forced dozens of airliners to change course. The FAA ended up expanding the aircraft hazard zone along Starship's launch trajectories before licensing future flights.
